Cellular heterogeneity and plasticity in liver cancer

Stemness regulation in prostate cancer: prostate cancer stem cells and targeted therapy

BACKGROUND

Increasing evidence indicates that cancer stem cells (CSCs) and cancer stem-like cells form a special subpopulation of cells that are ubiquitous in tumors. These cells exhibit similar characteristics to those of normal stem cells in tissues; moreover, they are capable of self-renewal and differentiation, as well as high tumorigenicity and drug resistance. In prostate cancer (PCa), it is difficult to kill these cells using androgen signaling inhibitors and chemotherapy drugs. Consequently, the residual prostate cancer stem cells (PCSCs) mediate tumor recurrence and progression.

OBJECTIVE

This review aims to provide a comprehensive and up-to-date overview of PCSCs, with a particular emphasis on potential therapeutic strategies targeting these cells.

METHODS

After searching in PubMed and Embase databases using 'prostate cancer' and 'cancer stem cells' as keywords, studies related were compiled and examined.

RESULTS

In this review, we detail the origin and characteristics of PCSCs, introduce the regulatory pathways closely related to CSC survival and stemness maintenance, and discuss the link between epithelial-mesenchymal transition, tumor microenvironment and tumor stemness. Furthermore, we introduce the currently available therapeutic strategies targeting CSCs, including signaling pathway inhibitors, anti-apoptotic protein inhibitors, microRNAs, nanomedicine, and immunotherapy. Lastly, we summarize the limitations of current CSC research and mention future research directions.

CONCLUSION

A deeper understanding of the regulatory network and molecular markers of PCSCs could facilitate the development of novel therapeutic strategies targeting these cells. Previous preclinical studies have demonstrated the potential of this treatment approach. In the future, this may offer alternative treatment options for PCa patients.

Autophagy-related gene SQSTM1 predicts the prognosis of hepatocellular carcinoma

BACKGROUND

The relationship between autophagy and the progression of hepatocellular carcinoma (HCC) is notably substantial, yet the underlying mechanisms remain incompletely elucidated. Our objective is to construct a predictive model, thereby providing fresh insights into the diagnosis and treatment of HCC. Autophagy's role in HCC progression is recognized, but the exact mechanisms are still unclear. This study seeks to build a predictive model to offer new diagnostic and therapeutic insights for HCC. Through combining bioinformatics and experiments, we aim to clarify autophagy pathways' part in HCC and spot possible treatment targets, thus aiding future HCC research and treatment.

METHODS

We screened HCC-related prognostic differential genes from the TCGA dataset combined with GeneCards, constructed a prognostic risk model related to autophagy genes and verified it in the GEO dataset and ICGC dataset. We integrated machine learning with protein-protein interaction (PPI) network analysis to pinpoint core targets and performed independent prognostic assessments. Leveraging single-cell sequencing data of hepatocellular carcinoma (HCC) from published literature, we ascertained the cellular distribution of these core genes.We used drug sensitivity analysis to screen clinical drugs for core genes.

RESULTS

We established a prognostic model using 12 differential prognostic genes, which was validated in both the GEO data set and the ICGC data set, and was more effective than the 5 collected prognostic models. Machine learning combined with the PPI network screened the core gene SQSTM1, and It can be a key factor in prognosis. Single-cell analysis showed that it is significantly distributed in Tumor-associated macrophages (TAM) where SQSTM1 is concentrated. Additionally, drug susceptibility analysis showed that patients with HCC and high SQSTM1 expression are responsive to 17-AGG.

CONCLUSIONS

Our study proposed a new risk model for predicting HCC patients based on autophagy-related genes (ARGs). The model has good predictive performance and screened out a potential target for HCC patients, which can be used as an independent prognostic factor. SQSTM1 was significantly enriched in tumor-associated macrophages. We also screened drugs for the treatment of hepatocellular carcinoma.

Exploring the Multifunctional Role of Alpha-Fetoprotein in Cancer Progression: Implications for Targeted Therapy in Hepatocellular Carcinoma and Beyond

Alpha-fetoprotein (AFP) is a well-known biomarker for liver cancer, and its clinical utility is widely recognized. Recent studies have revealed that AFP plays a multifaceted role in various malignant tumors, including liver cancer. This suggests that AFP is not merely a biomarker but also contributes significantly to the complex process of tumor formation, emphasizing the importance of targeting AFP in therapeutic approaches. Consequently, innovative research and development are essential to overcome the current limitations of AFP-targeted therapies, enhance treatment efficacy, and minimize side effects. This review explores the role of AFP in cancer development and progression, highlights the biological functions of AFP and related pathways, and discusses the clinical implications of AFP-targeted therapies. Ongoing research on AFP will significantly contribute to our understanding of the biological mechanisms of cancer and aid in developing effective and safe treatments. Ultimately, advancements in AFP-targeted therapeutic approaches are expected to play a crucial role in the future of cancer management.

Esculetin inhibits liver cancer by targeting glucose-6-phosphate isomerase mediated glycolysis

BACKGROUND

Liver cancer is challenging to detect in its early stages, and the global incidence rate and mortality associated with this disease have reached alarming levels. Currently, treatment options for liver cancer are limited, and there is a significant lack of safe and effective therapeutic agents. Esculetin is a natural product, exhibits almost non-toxic and inhibitory properties against various malignancies, making it a subject worthy of further investigation in liver cancer.

METHODS

In this study, potential targets of esculetin in liver cancer were identified through transcriptomics, network pharmacology, and molecular docking technologies, and gene interference. Direct binding targets of esculetin were identified using surface plasmon resonance (SPR). The molecular mechanisms by which esculetin affects glucose metabolism in liver cancer were also explored. Finally, the activity against liver cancer and mechanisms of action of esculetin were validated in vivo using a mouse tumor model.

RESULTS

Glucose-6-phosphate isomerase (GPI) was shown to have a direct binding affinity for this compound. Esculetin inhibits glycolysis in liver cancer through its interaction with GPI and it was shown to exert a significant inhibitory effect on the genes and proteins associated with glycolysis such as ALDOA, ENO1, GAPDH, LDHA, PFKL, PGAM1, PGK1, and PKM2. Furthermore, esculetin not only suppresses the growth of liver cancer cells in vitro but also exhibits notable anti-tumor effects in vivo.

CONCLUSIONS

This study demonstrated the inhibitory effects of esculetin against liver cancer both in vitro and in vivo, demonstrating inhibition of glycolysis in liver cancer cells. In addition, the key glycolysis enzyme GPI was identified as a direct target of esculetin.

Comprehensive analysis of immune subtype characterization on identification of potential cells and drugs to predict response to immune checkpoint inhibitors for hepatocellular carcinoma

Immunosubtyping enables the segregation of immune responders from non-responders. However, numerous studies failed to focus on the integration of cellular heterogeneity and immunophenotyping in the prediction of hepatocellular carcinoma (HCC) patients' response to immune checkpoint inhibitors (ICIs). We categorized HCC patients into various immune subtypes based on feature scores linked to ICI response. Single-cell sequencing technology was to investigate the cellular heterogeneity of different immune subtypes and acquire significant ICI response-associated cells. Candidate drugs were identified using a blend of various drug databases and network approaches. HCC patients were divided into two distinct immune subtypes based on characterization scores of 151 immune-related gene sets. Patients in both subtypes showed varying overall survival, immunity levels, biological activities, and TP53 mutation rates. Subtype 1-related natural killer cells showed a positive correlation with immune-promoting scores but a negative correlation with immune-suppressing scores. Notably, docetaxel sensitivity in HCC patients rose as the levels of subtype 1-related natural killer cells increased. Our study demonstrated that immune subtypes have cellular heterogeneity in predicting response to ICIs. A combination of subtype 1-associated natural killer cells and docetaxel may offer new hope for ICI treatment in HCC.

Lactate drives senescence-resistant lineages in hepatocellular carcinoma via histone H2B lactylation of NDRG1

Hepatocellular carcinoma (HCC) treatment options remain limited despite advances in targeted therapies for molecularly-defined cancers. To address tumor heterogeneity, we reconstructed HCC clonal evolution through single-cell RNA sequencing trajectory analysis, identifying 902 signature genes across seven cellular states. Weighted gene co-expression network analysis of public HCC datasets revealed tumor-grade-associated modules and established a 14-gene prognostic model linked to clonal evolution. Central to this model is the LDHA-NDRG1 axis - two hypoxia-responsive regulators showing coordinated spatiotemporal expression patterns during cancer progression. Dual-expressing cell lineages correlated with poor prognosis and senescence resistance through LDHA-mediated lactylation of histone H2B at K58 on NDRG1, an epigenetic mechanism connecting metabolic reprogramming to senescence evasion. Therapeutically, dual inhibition of this axis extended survival in metastatic HCC murine models. Our findings reveal that lactate-driven epigenetic modification via the LDHA-NDRG1 axis creates a molecularly distinct subpopulation enabling senescence resistance, providing mechanistic insights into HCC heterogeneity. This work proposes a precision medicine strategy targeting lactylation-mediated epigenetic regulation, with implications for developing combination therapies and patient stratification based on clonal evolution patterns.

MicroRNA-142-3p Overcomes Drug Resistance in Hepatocellular Carcinoma by Targeting YES1 and TWF1

Resistance to tyrosine kinase inhibitors (TKIs, e.g., sorafenib and lenvatinib) presents a significant hurdle for hepatocellular carcinoma (HCC) treatment, underscoring the need to decipher the underlying mechanisms for improved therapeutic strategies. MicroRNAs (miRNAs) have emerged as critical modulators in HCC progression and TKI resistance. In this study, we report a positive correlation between the expression levels of a tumor suppressor miRNA, miR-142-3p, and increased sensitivity to sorafenib and lenvatinib, supported by clinical data from the BIOSTORM HCC cohort. Overexpression of miR-142-3p in TKI-resistant HCC cells significantly inhibited proliferation and colony formation, induced apoptosis, increased cell cycle arrest at the G2 phase, and reduced migration and invasion by reversing epithelial-mesenchymal transition. Notably, combining miR-142-3p with lenvatinib synergistically inhibited growth in both inherent and acquired TKI-resistant HCC cells by modulating critical signaling pathways, including STAT3, PI3K/AKT, MAPK, YAP1, and by impeding autophagic influx. RNA-sequencing of a TKI-resistant HCC cell line ± miR-142-3p overexpression identified YES1 and TWF1 as direct downstream target genes of miR-142-3p, both of which are key genes associated with drug resistance in HCC. Small interfering RNA (siRNA)-mediated knockdown of these genes mirrored the antitumor effects of miR-142-3p and enhanced TKI sensitivity, with YES1 knockdown decreasing YAP1 phosphorylation, and TWF1 knockdown inhibiting autophagy. Collectively, these findings indicate that restoring miR-142-3p expression or targeting its downstream effectors YES1 and TWF1 offers a promising strategy to overcome drug resistance and improve therapeutic outcome in HCC.

Biological roles and clinical applications of EpCAM in HCC

Epithelial cell adhesion molecule (EpCAM) is an important biomarker in tumors. In hepatocellular carcinoma (HCC), EpCAM + cells exhibit high invasiveness, tumorigenic ability, therapeutic resistance, and self-renewal ability, often identified as liver cancer stem cells (CSCs). Detecting EpCAM + cells in tumor lesions and circulation is valuable for predicting patient prognosis and monitoring therapeutic outcomes, emphasizing its clinical significance. Given its broad expression in HCC, especially in CSCs and circulating tumor cells (CTCs), EpCAM-targeting agents have garnered substantial research interest. However, the role of EpCAM in HCC progression and its regulatory mechanisms remains poorly understood. Furthermore, clinical applications of EpCAM, such as liquid biopsy and targeted therapies, are still controversial. This review summarizes the biological properties of EpCAM + HCC cells, explores the regulatory mechanisms governing EpCAM expression, and discusses its clinical significance of using EpCAM as a prognostic marker and therapeutic target.

SLC7A11, a disulfidptosis-related gene, correlates with multi-omics prognostic analysis in hepatocellular carcinoma

BACKGROUND

This study sought to establish a risk score signature based on disulfidptosis-related genes (DRGs) to predict the prognosis of hepatocellular carcinoma (HCC) patients.

METHODS

The expression data of DRGs from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) was analyzed to develop and validate a DRG prognostic signature (DRGPS). In vitro, experiments were conducted to explore DRG expressions and roles in HCC tissues and cell lines. HCC tissue microarrays were employed to analyze SLC7A11 expression and its association with clinicopathological characteristics.

RESULTS

The DRGPS consisted of 5 DRGs (SLC7A11, MATN3, CLEC3B, CCNJL, and PON1). The survival rate of HCC patients in high-risk group was significantly lower than that in low-risk group. The DRGPS was also associated with the modulation of tumor microenvironment (TME), tumor mutation burden (TMB), stemness and chemosensitivity. Furthermore, pan-cancer analysis suggested that the DRGPS risk score was associated with immune infiltration and stemness in multiple cancers. Moreover, our DRGPS had potential for predicting treatment efficacy in HCC patients. Finally, we confirmed that downregulation of SLC7A11, a DRG, inhibited the proliferation and migration of HCC cells, while its high expression correlated with advanced TNM clinical stage and larger tumor size.

CONCLUSIONS

This study systematically describes a novel DRGPS constructed for predicting HCC prognosis, providing a new approach to risk stratification and treatment options. It also investigates the expression and function of SLC7A11, contributing to further exploration of the molecular mechanism underlying disulfidptosis in HCC, as well as its prognostic and therapeutic implications.

Regulation of KIF23 by miR-107 controls replicative tumor cell fitness in mouse and human hepatocellular carcinoma

BACKGROUND & AIMS

In hepatocellular carcinoma (HCC), successful translation of experimental targets identified in mouse models to human patients has proven challenging. In this study, we used a comprehensive transcriptomic approach in mice to identify novel potential targets for therapeutic intervention in humans.

METHODS

We analyzed combined genome-wide miRNA and mRNA expression data in three pathogenically distinct mouse models of liver cancer. Effects of target genes on hepatoma cell fitness were evaluated by proliferation, survival and motility assays. TCGA and GEO databases, in combination with tissue microarrays, were used to validate the mouse targets and their impact on human HCC prognosis. Finally, the functional effects of the identified targets on tumorigenesis and tumor therapy were tested in hydrodynamic tail vein injection-based preclinical HCC models in vivo.

RESULTS

The expression of miR-107 was found to be significantly reduced in mouse models of liver tumors of various etiologies and in cohorts of humans with HCC. Overexpression of miR-107 or inhibition of its novel target kinesin family member 23 (Kif23) significantly reduced proliferation by interfering with cytokinesis, thereby controlling survival and motility of mouse and human hepatoma cells. In humans, KIF23 expression was found to be a prognostic marker in liver cancer, with high expression associated with poor prognosis. Hydrodynamic tail vein injection of vectors carrying either pre-miR-107 or anti-Kif23 shRNA inhibited the development of highly aggressive c-Myc-NRAS-induced liver cancers in mice.

CONCLUSIONS

Disruption of the miR-107/Kif23 axis inhibited hepatoma cell proliferation in vitro and prevented oncogene-induced liver cancer development in vivo, offering a novel potential avenue for the treatment of HCC in humans.

IMPACT AND IMPLICATIONS

Our study revealed the central role of the miR-107/KIF23 axis in controlling tumor cell fitness and hepatocellular carcinoma progression. The results demonstrate that the overexpression of miR-107 or silencing of its target, KIF23, markedly suppresses the proliferation, survival, and motility of human and mouse hepatoma cells. In this work, we demonstrate that the disruption of miR-107/Kif23 signaling effectively protects mice from an aggressive form of oncogene-induced liver cancer in vivo, implying that targeting miR-107/KIF23 might be a novel therapeutic approach for hepatocellular carcinoma in humans.

HepatoPredict Accurately Selects Hepatocellular Carcinoma Patients for Liver Transplantation Regardless of Tumor Heterogeneity

BACKGROUND/OBJECTIVES

Hepatocellular carcinoma (HCC) is a major cause of cancer-related deaths rising worldwide. This is leading to an increased demand for liver transplantation (LT), the most effective treatment for HCC in its initial stages. However, current patient selection criteria are limited in predicting recurrence and raise ethical concerns about equitable access to care. This study aims to enhance patient selection by refining the HepatoPredict (HP) tool, a machine learning-based model that combines molecular and clinical data to forecast LT outcomes.

METHODS

The updated HP algorithm was trained on a two-center dataset and assessed against standard clinical criteria. Its prognostic performance was evaluated through accuracy metrics, with additional analyses considering tumor heterogeneity and potential sampling bias.

RESULTS

HP outperformed all clinical criteria, particularly regarding negative predictive value, addressing critical limitations in existing selection strategies. It also demonstrated improved differentiation of recurrence-free and overall survival outcomes. Importantly, the prognostic accuracy of HP remained largely unaffected by intra-nodule and intra-patient heterogeneity, indicating its robustness even when biopsies were taken from smaller or non-dominant nodules.

CONCLUSIONS

These findings support the usage of HP as a valuable tool for optimizing LT candidate selection, promoting fair organ allocation and enhancing patient outcomes through integrated analysis of molecular and clinical data.

Association of dietary intake with cancer of the digestive system: a cross-sectional study

Background

In recent years, the incidence of cancers of the digestive system has been increasing, posing a severe threat to the lives and health of people around the world, and has become one of the leading causes of cancer deaths worldwide. The three most common cancers of the digestive system include gastric, colorectal, and liver cancers, and attention has been paid to the role of diet in the progression of these cancers. However, the relationship between dietary factors and cancers of the digestive system remains to be investigated.

Methods

This study included 30,789 adults aged 20 years or older from the National Health and Nutrition Examination Survey (NHANES), conducted from 2007 to 2018. It assessed the association between 30 dietary factors and digestive system cancers. Descriptive analysis was used to explore the demographic characteristics of the participants and p-values were calculated using a weighted linear regression model. Categorical variables were described as percentages, and p-values were calculated using weighted chi-square tests.

Results

We found that protein, vitamin B1, calcium, and iron intake were positively associated with colorectal cancer; vitamin B2 and phosphorus intake were negatively related to colorectal cancer; dietary folate and vitamin B12 intake were negatively associated with gastric cancer; vitamin D and copper intake were positively associated with gastric cancer; vitamin E intake was negatively related to the development of hepatocellular carcinoma; and lycopene, vitamin B2, calcium, iron, and zinc intake was positively associated with the development of liver cancer. Other than that, we did not observe any correlation between other dietary factors and cancers of the digestive system.

Conclusion

Dietary intake is associated with digestive system cancers, and more epidemiologic studies are needed to validate our results.

In silico analysis of lncRNA-miRNA-mRNA signatures related to Sorafenib effectiveness in liver cancer cells

BACKGROUND

Hepatocellular carcinoma (HCC) is the most common subtype of primary liver cancer with varied incidence and epidemiology worldwide. Sorafenib is still a recommended treatment for a large proportion of patients with advanced HCC. Different patterns of treatment responsiveness have been identified in differentiated hepatoblastoma HepG2 cells and metastatic HCC SNU449 cells.

AIM

To define the long non-codingRNA-microRNA-mRNA (lncRNA-miRNA-mRNA) predicted signatures related to selected hallmarks of cancer (apoptosis, autophagy, cell stress, cell dedifferentiation and invasiveness) in RNAseq studies using Sorafenib-treated HepG2 and SNU449 cells. Various available software analyses allowed us to establish the lncRNA-miRNA-mRNA regulatory axes following treatment in HepG2 and SNU449 cells.

METHODS

HepG2 and SNU449 cells were treated with Sorafenib (10 μmol/L) for 24 hours. Total RNA, including small and long RNA, was extracted with a commercial miRNeasy kit. RNAseq was carried out for the identification of changes in lncRNA-miRNA-mRNA regulatory axes.

RESULTS

MALAT, THAP9-AS1 and SNGH17 appeared to coordinately regulate miR-374b-3p and miR-769-5p that led to upregulation of SMAD7, TIRARP, TFAP4 and FAXDC2 in HepG2 cells. SNHG12, EPB41 L4A-AS1, LINC01578, SNHG12 and GAS5 interacted with let-7b-3p, miR-195-5p and VEGFA in SNU449 cells. The axes MALAT1/hsa-mir-374b-3p/SMAD7 and MALAT1/hsa-mir-769-5p/TFAP4 were of high relevance for Sorafenib response in HepG2 cells, whereas PVT1/hsa-miR-195-5p/VEGFA was responsible for the differential response of SNU449 cells to Sorafenib treatment.

CONCLUSION

Critical lncRNAs acting as sponges of miRNA were identified that regulated mRNA expression, whose proteins mainly increased the antitumor effectiveness of the treatment (SMAD7, TIRARP, TFAP4, FAXDC2 and ADRB2). However, the broad regulatory axis leading to increased VEGFA expression may be related to the side effect of Sorafenib in SNU449 cells.

Design, Synthesis, and Antitumor Activity Evaluation of 2-Phenylthiazole-5-Carboxylic Acid Derivatives Targeting Transactivation Response RNA-Binding Protein 2

Transactivation response (TAR) RNA-binding protein 2 (TRBP) plays a critical role in microRNA (miRNA) biosynthesis, with aberrant expression linked to various cancers. Previously, we identified CIB-3b, a phenyloxazole derivative that disrupts the TRBP-Dicer interaction in hepatocellular carcinoma (HCC). In this study, we optimized this scaffold and substituent, leading to the discovery of CIB-L43, a 2-phenylthiazole-5-carboxylic acid derivative with nanomolar inhibitory activity (EC50 = 0.66 nM). CIB-L43 demonstrated superior TRBP binding affinity (KD = 4.78 nM) and enhanced disruption of TRBP-Dicer interactions (IC50 = 2.34 μM). Mechanistically, CIB-L43 suppressed oncogenic miR-21 biosynthesis, increasing PTEN and Smad7 expression and inhibiting AKT and TGF-β signaling, thereby reducing HCC cell proliferation and migration. In vivo, CIB-L43 exhibited favorable pharmacokinetics, including 53.9% oral bioavailability, and comparable antitumor efficacy to first-line anticancer drug, sorafenib, with lower toxicity. CIB-L43 emerges as a promising HCC treatment candidate with potent TRBP inhibition and favorable drug-like properties.

miR-10b-5p promotes tumor growth by regulating cell metabolism in liver cancer via targeting SLC38A2

Metabolic reprogramming plays a critical role in hepatocarcinogenesis. However, the mechanisms regulating metabolic reprogramming in primary liver cancer (PLC) are unknown. Differentially expressed miRNAs between PLC and normal tissues were identified using bioinformatic analysis. RT-qPCR was used to determine miR-10b-5p and SCL38A2 expression levels. IHC, WB, and TUNEL assays were used to assess the proliferation and apoptosis of the tissues. The proliferation, migration, invasion, and apoptosis of PLC cells were determined using the CCK-8 assay, Transwell assay, and flow cytometry. The interaction between miR-10b-5p and SLC38A2 was determined using dual-luciferase reporter assay. A PLC xenograft model in BALB/c nude mice was established, and tumorigenicity and SLC38A2 expression were estimated. Finally, liquid chromatography - mass spectrometry (LC-MS) untargeted metabolomics was used to analyze the metabolic profiles of xenograft PLC tissues in nude mice. miR-10b-5p was a key molecule in the regulation of PLC. Compared with para-carcinoma tissues, miR-10b-5p expression was increased in tumor tissues. miR-10b-5p facilitated proliferation, migration, and invasion of PLC cells. Mechanistically, miR-10b-5p targeted SLC38A2 to promote PLC tumor growth. Additionally, miR-10b-5p altered the metabolic features of PLC in vivo. Overexpression of miR-10b-5p resulted in remarkably higher amounts of lumichrome, folic acid, octanoylcarnitine, and Beta-Nicotinamide adenine dinucleotide, but lower levels of 2-methylpropanal, glycyl-leucine, and 2-hydroxycaproic acid. miR-10b-5p facilitates the metabolic reprogramming of PLC by targeting SLC38A2, which ultimately boosts the proliferation, migration, and invasion of PLC cells. Therefore, miR-10b-5p and SLC38A2 are potential targets for PLC diagnosis and treatment.

Loss of LRP1 Promotes Hepatocellular Carcinoma Progression via UFL1-Mediated Activation of NF-κB Signaling

Low-density lipoprotein receptor-related protein-1 (LRP1) is thought to be correlated with hepatocellular carcinoma (HCC) invasion and metastasis. However, the precise mechanism through which LRP1 contributes to HCC progression remains unclear. Here, lower LRP1 levels are associated with malignant progression, and poor prognosis in patients with HCC is shown. LRP1 knockdown enhances the tumorigenicity of HCC cells in vitro and in vivo, whereas overexpression of either LRP1 or its β-chain has the opposite effect. Mechanistically, LRP1 knockdown promotes the binding of ubiquitin-like modifier 1 ligating enzyme 1 (UFL1) to OGA and accelerates ubiquitin-mediated OGA degradation, leading to increased O-GlcNAcylation of nuclear factor-kappa B (NF-κB) and subsequent inhibition of pro-apoptotic gene expression. Conversely, exogenously expressed truncated β-chain (β∆) stabilizes OGA by disrupting the association between UFL1 and OGA, consequently abolishing the anti-apoptotic effects of O-GlcNAcylated NF-κB. The findings identify LRP1, particularly its β-chain, as a novel upstream control factor that facilitates the stabilization of the OGA protein, thereby suppressing NF-κB signaling and attenuating HCC progression, thus suggesting a novel therapeutic strategy for HCC.

Evolutionary View of Liver Pathology

Evolutionary medicine emerged in the late twentieth century, integrating principles of natural selection and adaptation with the health sciences. Today, with a rapidly widening gap between the biology of Homo sapiens and its environment, maladaptation or maladaptive disorders can be detected in almost all diseases, including liver dysfunction. However, in hepatology, as in most medical specialties, evolutionary considerations are neglected because the majority of the medical community is not familiar with evolutionary principles. The aim of this brief review is to highlight an evolutionary approach that may facilitate understanding various liver diseases.

LiverSCA: A comprehensive and user-friendly cell atlas in human hepatocellular carcinoma

We developed a cell atlas named LiverSCA on human liver cancer single-cell RNA sequencing data. It has a user-friendly web interface and comprehensive functionalities aiming to help researchers to make easy access to cellular and molecular landscapes of the tumor microenvironment in liver cancer. LiverSCA includes a complete analytical pipeline that allow mechanistic exploration on a wide variety of functionalities, such as cell clustering, cell annotation, identification of differentially expressed genes, functional enrichment analysis, analysis of cellular crosstalk, and pseudo-time trajectory analysis. Notably, our intuitive web interface allows users, particularly wet-lab researchers, to easily explore and undertake data discovery, without the need to handle any of the raw data.

miRNAs in HCC, pathogenesis, and targets

Liver cancer is the third leading cause of cancer-related mortality worldwide. HCC, the most common type of primary liver cancer, is driven by complex genetic, epigenetic, and environmental factors. MicroRNAs, a class of naturally occurring small noncoding RNAs, play crucial roles in HCC by simultaneously modulating the expression of multiple genes in a fine-tuning manner. Significant progress has been made in understanding how miRNAs influence key oncogenic pathways, including cell proliferation, apoptosis, angiogenesis, and epithelial-mesenchymal transition (EMT), as well as their role in modulating the immune microenvironment in HCC. Due to the unexpected stability of miRNAs in the blood and fixed HCC tumors, recent advancements also highlight their potential as noninvasive diagnostic tools. Restoring or inhibiting specific miRNAs has offered promising strategies for targeted HCC treatment by suppressing malignant hepatocyte growth and enhancing antitumor immunity. In this comprehensive review, we consolidate previous research and provide the latest insights into how miRNAs regulate HCC and their therapeutic and diagnostic potential. We delve into the dysregulation of miRNA biogenesis in HCC, the roles of miRNAs in the proliferation and apoptosis of malignant hepatocytes, angiogenesis and metastasis of HCC, the immune microenvironment in HCC, and drug resistance. We also discuss the therapeutic and diagnostic potential of miRNAs and delivery approaches of miRNA drugs to overcome the limitations of current HCC treatment options. By thoroughly summarizing the roles of miRNAs in HCC, our goal is to advance the development of effective therapeutic drugs with minimal adverse effects and to establish precise tools for early diagnosis of HCC.

Babaodan inhibits cell proliferation and metastasis and enhances anti-tumor effects of camrelizumab by inhibiting M2 phenotype macrophages in hepatocellular carcinoma

ETHNOPHARMACOLOGICAL RELEVANCE

Babaodan (BBD) is a unique Chinese medication utilized in traditional Chinese medicine. It can eliminate toxins, induce diuresis, and eliminate yellowish hue. In addition to treating acute and chronic viral hepatitis, cholecystitis, cholangitis, and urinary tract infections, BBD has garnered popularity as a substitution treatment for several malignant cancers, particularly hepatocellular carcinoma (HCC).

AIM OF THE STUDY

To elucidate the efficacy and mechanism of BBD alone and combined with camrelizumab (CLM) for treating HCC.

METHODS

We investigated the effects of BBD on the HCC tumor microenvironment in vivo. Furthermore, we evaluated its effects on tumor growth and metastasis induced by M2 macrophages in vitro.

RESULTS

In a mouse model of orthotopic HCC, BBD decreased tumor growth. Furthermore, it increased the M1/M2 macrophage ratio and CD8+ T-cell abundance in mice. In addition, BBD reversed HCC cell proliferation and metastasis induced by M2 macrophages, increased the anti-HCC effect of low-dose CLM, and attenuated organ damage induced by high-dose CLM. Lastly, BBD enhanced the efficacy of CLM via the PI3K/AKT/mTOR signaling pathway.

CONCLUSION

BBD increases the antitumor effect of CLM by modulating the tumor immune microenvironment and attenuating its the toxic side effects of CLM.

Single-cell RNA sequencing reveals the landscape of the cellular ecosystem of primary hepatocellular carcinoma

Hepatocellular carcinoma (HCC) cells, along with multiple nonmalignant stromal cells, such as fibroblasts, endothelial cells and immune cells, comprise an intricate cellular ecosystem, undergo dynamic phenotypic changes and present complicated cellular interactions, thus synergistically facilitating HCC initiation and progression and leading to treatment resistance. Clarifying the heterogeneity, cell plasticity and complexity of the cellular ecosystem of HCC will be highly beneficial for understanding HCC development and identifying novel therapeutic targets. Single-cell RNA sequencing (scRNA-seq) refers to profiling the transcriptome at single-cell resolution, and the development of scRNA-seq technology and analysis algorithms has greatly promoted the analysis of cell composition, cell subpopulation heterogeneity, development trajectory and cell-to-cell interactions in cell populations. In this review, we systematically summarized and discussed scRNA-seq in treatment-naive primary HCC and revealed the global cell composition of HCC; the widespread molecular heterogeneity of HCC cells; the molecular subtypes of fibroblasts; the cell composition, functional states and development trajectory of immune cells; and the frequent interactions between different cell types to systematically draw the landscape of the cellular ecosystem of primary HCC.

Intratumoral microbiota: an emerging force in diagnosing and treating hepatocellular carcinoma

Hepatocellular carcinoma (HCC) ranks among the most prevalent types of cancer in the world and its incidence and mortality are increasing year by year, frequently diagnosed at an advanced stage. Traditional treatments such as surgery, chemotherapy, and radiotherapy have limited efficacy, so new diagnostic and treatment strategies are urgently needed. Recent research has discovered that intratumoral microbiota significantly influences the development, progression, and metastasis of HCC by modulating inflammation, immune responses, and cellular signaling pathways. Intratumoral microbiota contributes to the pathologic process of HCC by influencing the tumor microenvironment and altering the function of immune system. This article reviews the mechanism of intratumoral microbiota in HCC and anticipates the future possibilities of intratumoral microbiota-based therapeutic strategies for HCC management. This emerging field provides fresh insights into early diagnosis and personalized approaches for HCC while holding substantial clinical application potential to improve patient outcomes and tailor interventions to individual tumor profiles.

Application of a single-cell-RNA-based biological-inspired graph neural network in diagnosis of primary liver tumors

Single-cell technology depicts integrated tumor profiles including both tumor cells and tumor microenvironments, which theoretically enables more robust diagnosis than traditional diagnostic standards based on only pathology. However, the inherent challenges of single-cell RNA sequencing (scRNA-seq) data, such as high dimensionality, low signal-to-noise ratio (SNR), sparse and non-Euclidean nature, pose significant obstacles for traditional diagnostic approaches. The diagnostic value of single-cell technology has been largely unexplored despite the potential advantages. Here, we present a graph neural network-based framework tailored for molecular diagnosis of primary liver tumors using scRNA-seq data. Our approach capitalizes on the biological plausibility inherent in the intercellular communication networks within tumor samples. By integrating pathway activation features within cell clusters and modeling unidirectional inter-cellular communication, we achieve robust discrimination between malignant tumors (including hepatocellular carcinoma, HCC, and intrahepatic cholangiocarcinoma, iCCA) and benign tumors (focal nodular hyperplasia, FNH) by scRNA data of all tissue cells and immunocytes only. The efficacy to distinguish iCCA from HCC was further validated on public datasets. Through extending the application of high-throughput scRNA-seq data into diagnosis approaches focusing on integrated tumor microenvironment profiles rather than a few tumor markers, this framework also sheds light on minimal-invasive diagnostic methods based on migrating/circulating immunocytes.

Biomarkers for Immunotherapy Efficacy in Advanced Hepatocellular Carcinoma: A Comprehensive Review

Hepatocellular carcinoma (HCC), the most common primary liver malignancy and the sixth most common cancer globally, remains fatal for many patients with inappropriate responses to treatment. Recent advancements in immunotherapy have transformed the treatment landscape for advanced HCC. However, variability in patient responses to immunotherapy highlights the need for biomarkers that can predict treatment outcomes. This manuscript comprehensively reviews the evolving role of biomarkers in immunotherapy efficacy, spanning from blood-derived indicators-alpha-fetoprotein, inflammatory markers, cytokines, circulating tumor cells, and their DNA-to tissue-derived indicators-programmed cell death ligand 1 expression, tumor mutational burden, microsatellite instability, and tumor-infiltrating lymphocytes. The current body of evidence suggests that these biomarkers hold promise for improving patient selection and predicting immunotherapy outcomes. Each biomarker offers unique insights into disease biology and the immune landscape of HCC, potentially enhancing the precision of treatment strategies. However, challenges such as methodological variability, high costs, inconsistent findings, and the need for large-scale validation in well-powered two-arm trial studies persist, making them currently unsuitable for integration into standard care. Addressing these challenges through standardized techniques and implementation of further studies will be critical for the future incorporation of these biomarkers into clinical practice for advanced HCC.

Sorafenib-mediated cleavage of p62 initiates cellular senescence as a mechanism to evade its anti-hepatocellular carcinoma efficacy

Hepatocellular carcinoma (HCC) stands as one of the most aggressively advancing and lethal malignancies. Sorafenib is presently endorsed as a primary therapy for advanced liver cancer, but its resistance presents a formidable challenge. Previous studies have implicated a connection between post-sorafenib discontinuation rebound and the development of drug resistance, yet the underlying mechanism remains elusive. In this study, we discerned that Sorafenib induced a senescent phenotype in HCC cells and caused a cleavage of ubiquitin-binding protein p62. Mechanistic studies establish that truncated p62 drives cellular senescence by promoting proteasome-dependent degradation of 4EBP1. Furthermore, truncated p62 induced specific ubiquitination of 4EBP1. Crucially, virtual drug screening uncovered that dacinostat inhibited cellular senescence by blocking sorafenib-induced p62 cleavage. In summary, our findings imply that truncated p62 from sorafenib cleavage promotes senescence via 4EBP1 degradation. The prevention of p62 cleavage could emerge as a crucial strategy for impeding the sorafenib-induced cellular senescence.

MicroRNAs in Hepatocellular Carcinoma Pathogenesis: Insights into Mechanisms and Therapeutic Opportunities

Hepatocellular carcinoma (HCC) presents a significant global health burden, with alarming statistics revealing its rising incidence and high mortality rates. Despite advances in medical care, HCC treatment remains challenging due to late-stage diagnosis, limited effective therapeutic options, tumor heterogeneity, and drug resistance. MicroRNAs (miRNAs) have attracted substantial attention as key regulators of HCC pathogenesis. These small non-coding RNA molecules play pivotal roles in modulating gene expression, implicated in various cellular processes relevant to cancer development. Understanding the intricate network of miRNA-mediated molecular pathways in HCC is essential for unraveling the complex mechanisms underlying hepatocarcinogenesis and developing novel therapeutic approaches. This manuscript aims to provide a comprehensive review of recent experimental and clinical discoveries regarding the complex role of miRNAs in influencing the key hallmarks of HCC, as well as their promising clinical utility as potential therapeutic targets.

Heterogeneity of hepatocellular carcinoma: from mechanisms to clinical implications

Hepatocellular Carcinoma (HCC) is one of the most common types of primary liver cancer. Current treatment options have limited efficacy against this malignancy, primarily owing to difficulties in early detection and the inherent resistance to existing drugs. Tumor heterogeneity is a pivotal factor contributing significantly to treatment resistance and recurrent manifestations of HCC. Intratumoral heterogeneity is an important aspect of the spectrum of complex tumor heterogeneity and contributes to late diagnosis and treatment failure. Therefore, it is crucial to thoroughly understand the molecular mechanisms of how tumor heterogeneity develops. This review aims to summarize the possible molecular dimensions of tumor heterogeneity with an emphasis on intratumoral heterogeneity, evaluate its profound impact on the diagnosis and therapeutic strategies for HCC, and explore the suitability of appropriate pre-clinical models that can be used to best study tumor heterogeneity; thus, opening new avenues for cancer treatment.

Development and Validation of a Carbohydrate Metabolism-Related Model for Predicting Prognosis and Immune Landscape in Hepatocellular Carcinoma Patients

OBJECTIVE

The activities and products of carbohydrate metabolism are involved in key processes of cancer. However, its relationship with hepatocellular carcinoma (HCC) is unclear.

METHODS

The cancer genome atlas (TCGA)-HCC and ICGC-LIRI-JP datasets were acquired via public databases. Differentially expressed genes (DEGs) between HCC and control samples in the TCGA-HCC dataset were identified and overlapped with 355 carbohydrate metabolism-related genes (CRGs) to obtain differentially expressed CRGs (DE-CRGs). Then, univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses were applied to identify risk model genes, and HCC samples were divided into high/low-risk groups according to the median risk score. Next, gene set enrichment analysis (GSEA) was performed on the risk model genes. The sensitivity of the risk model to immunotherapy and chemotherapy was also explored.

RESULTS

A total of 8 risk model genes, namely, G6PD, PFKFB4, ACAT1, ALDH2, ACYP1, OGDHL, ACADS, and TKTL1, were identified. Moreover, the risk score, cancer status, age, and pathologic T stage were strongly associated with the prognosis of HCC patients. Both the stromal score and immune score had significant negative/positive correlations with the risk score, reflecting the important role of the risk model in immunotherapy sensitivity. Furthermore, the stromal and immune scores had significant negative/positive correlations with risk scores, reflecting the important role of the risk model in immunotherapy sensitivity. Eventually, we found that high-/low-risk patients were more sensitive to 102 drugs, suggesting that the risk model exhibited sensitivity to chemotherapy drugs. The results of the experiments in HCC tissue samples validated the expression of the risk model genes.

CONCLUSION

Through bioinformatic analysis, we constructed a carbohydrate metabolism-related risk model for HCC, contributing to the prognosis prediction and treatment of HCC patients.

Advances in Single-Cell Techniques for Linking Phenotypes to Genotypes

Single-cell analysis has become an essential tool in modern biological research, providing unprecedented insights into cellular behavior and heterogeneity. By examining individual cells, this approach surpasses conventional population-based methods, revealing critical variations in cellular states, responses to environmental cues, and molecular signatures. In the context of cancer, with its diverse cell populations, single-cell analysis is critical for investigating tumor evolution, metastasis, and therapy resistance. Understanding the phenotype-genotype relationship at the single-cell level is crucial for deciphering the molecular mechanisms driving tumor development and progression. This review highlights innovative strategies for selective cell isolation based on desired phenotypes, including robotic aspiration, laser detachment, microraft arrays, optical traps, and droplet-based microfluidic systems. These advanced tools facilitate high-throughput single-cell phenotypic analysis and sorting, enabling the identification and characterization of specific cell subsets, thereby advancing therapeutic innovations in cancer and other diseases.

Bispecific CAR-T cells targeting FAP and GPC3 have the potential to treat hepatocellular carcinoma

Chimeric antigen receptor (CAR) T cell therapy has demonstrated robust efficacy against hematological malignancies, but there are still some challenges regarding treating solid tumors, including tumor heterogeneity, antigen escape, and an immunosuppressive microenvironment. Here, we found that SNU398, a hepatocellular carcinoma (HCC) cell line, exhibited high expression levels of fibroblast activation protein (FAP) and Glypican 3 (GPC3), which were negatively correlated with patient prognosis. The HepG2 HCC cell line highly expressed GPC3, while the SNU387 cell line exhibited high expression of FAP. Thus, we developed bispecific CAR-T cells to simultaneously target FAP and GPC3 to address tumor heterogeneity in HCC. The anti-FAP-GPC3 bispecific CAR-T cells could recognize and be activated by FAP or GPC3 expressed by tumor cells. Compared with anti-FAP CAR-T cells or anti-GPC3 CAR-T cells, bispecific CAR-T cells achieved more robust activity against tumor cells expressing FAP and GPC3 in vitro. The anti-FAP-GPC3 bispecific CAR-T cells also exhibited superior antitumor efficacy and significantly prolonged the survival of mice compared with single-target CAR-T cells in vivo. Overall, the use of anti-FAP-GPC3 bispecific CAR-T cells is a promising treatment approach to reduce tumor recurrence caused by tumor antigen heterogeneity.

FGL1 and FGL2: emerging regulators of liver health and disease

Liver disease is a complex group of diseases with high morbidity and mortality rates, emerging as a major global health concern. Recent studies have highlighted the involvement of fibrinogen-like proteins, specifically fibrinogen-like protein 1 (FGL1) and fibrinogen-like protein 2 (FGL2), in the regulation of various liver diseases. FGL1 plays a crucial role in promoting hepatocyte growth, regulating lipid metabolism, and influencing the tumor microenvironment (TME), contributing significantly to liver repair, non-alcoholic fatty liver disease (NAFLD), and liver cancer. On the other hand, FGL2 is a multifunctional protein known for its role in modulating prothrombin activity and inducing immune tolerance, impacting viral hepatitis, liver fibrosis, hepatocellular carcinoma (HCC), and liver transplantation. Understanding the functions and mechanisms of fibrinogen-like proteins is essential for the development of effective therapeutic approaches for liver diseases. Additionally, FGL1 has demonstrated potential as a disease biomarker in radiation and drug-induced liver injury as well as HCC, while FGL2 shows promise as a biomarker in viral hepatitis and liver transplantation. The expression levels of these molecules offer exciting prospects for disease assessment. This review provides an overview of the structure and roles of FGL1 and FGL2 in different liver conditions, emphasizing the intricate molecular regulatory processes and advancements in targeted therapies. Furthermore, it explores the potential benefits and challenges of targeting FGL1 and FGL2 for liver disease treatment and the prospects of fibrinogen-like proteins as biomarkers for liver disease, offering insights for future research in this field.

Construction of diagnostic models for the progression of hepatocellular carcinoma using machine learning

Liver cancer is one of the most prevalent forms of cancer worldwide. A significant proportion of patients with hepatocellular carcinoma (HCC) are diagnosed at advanced stages, leading to unfavorable treatment outcomes. Generally, the development of HCC occurs in distinct stages. However, the diagnostic and intervention markers for each stage remain unclear. Therefore, there is an urgent need to explore precise grading methods for HCC. Machine learning has emerged as an effective technique for studying precise tumor diagnosis. In this research, we employed random forest and LightGBM machine learning algorithms for the first time to construct diagnostic models for HCC at various stages of progression. We categorized 118 samples from GSE114564 into three groups: normal liver, precancerous lesion (including chronic hepatitis, liver cirrhosis, dysplastic nodule), and HCC (including early stage HCC and advanced HCC). The LightGBM model exhibited outstanding performance (accuracy = 0.96, precision = 0.96, recall = 0.96, F1-score = 0.95). Similarly, the random forest model also demonstrated good performance (accuracy = 0.83, precision = 0.83, recall = 0.83, F1-score = 0.83). When the progression of HCC was categorized into the most refined six stages: normal liver, chronic hepatitis, liver cirrhosis, dysplastic nodule, early stage HCC, and advanced HCC, the diagnostic model still exhibited high efficacy. Among them, the LightGBM model exhibited good performance (accuracy = 0.71, precision = 0.71, recall = 0.71, F1-score = 0.72). Also, performance of the LightGBM model was superior to that of the random forest model. Overall, we have constructed a diagnostic model for the progression of HCC and identified potential diagnostic characteristic gene for the progression of HCC.

Multimodal Imaging-Guided Synergistic Photodynamic Therapy Using Carbonized Zn/Co Metal-Organic Framework Loaded with Cytotoxin Against Liver Cancer

Purpose

The study aimed to address the non-specific toxicity of cytotoxins (CTX) in liver cancer treatment and explore their combined application with the photosensitizer Ce6, co-loaded into carbonized Zn/Co bimetallic organic frameworks. The goal was to achieve controlled CTX release and synergistic photodynamic therapy, with a focus on evaluating anti-tumor activity against human liver cancer cell lines (Hep G2).

Methods

Purified cobra cytotoxin (CTX) and photosensitizer Ce6 were co-loaded into carbonized Zn/Co bimetallic organic frameworks, resulting in RGD-PDA@C-ZIF@(CTX+Ce6). The formulation was designed with surface-functionalization using polydopamine and tumor-penetrating peptide RGD. This approach aimed to facilitate controlled CTX release and enhance the synergistic effect of photodynamic therapy. The accumulation of RGD-PDA@C-ZIF@(CTX+Ce6) at tumor sites was achieved through RGD's active targeting and the enhanced permeability and retention (EPR) effect. In the acidic tumor microenvironment, the porous structure of the metal-organic framework disintegrated, releasing CTX and Ce6 into tumor cells.

Results

Experiments demonstrated that RGD-PDA@C-ZIF@(CTX+Ce6) nanoparticles, combined with near-infrared laser irradiation, exhibited optimal anti-tumor effects against human liver cancer cells. The formulation showcased heightened anti-tumor activity without discernible systemic toxicity.

Conclusion

The study underscores the potential of utilizing metal-organic frameworks as an efficient nanoplatform for co-loading cytotoxins and photodynamic therapy in liver cancer treatment. The developed formulation, RGD-PDA@C-ZIF@(CTX+Ce6), offers a promising avenue for advancing the clinical application of cytotoxins in oncology, providing a solid theoretical foundation for future research and development.

Role of CENPF and NDC80 in the rehabilitation nursing of hepatocellular carcinoma and cirrhosis: An observational study

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors globally and often develops on the foundation of chronic liver disease or cirrhosis. Cirrhosis is a clinically prevalent chronic progressive liver disease characterized by diffuse liver damage resulting from long-term or repeated actions of 1 or more etiological factors. However, the impact of CENPF and nuclear division cycle 80 (NDC80) genes on rehabilitation nursing of HCC and cirrhosis remains unclear. HCC and cirrhosis datasets GSE63898 and GSE89377 profile files were downloaded from the gene expression omnibus database generated on platforms GPL13667 and GPL6947, respectively. Differentially expressed genes (DEGs) screening, weighted gene co-expression network analysis (WGCNA), construction and analysis of protein-protein interaction (PPI) networks, functional enrichment analysis, gene set enrichment analysis (GSEA), survival analysis, immune infiltration analysis, and comparative toxicogenomics database (CTD) analysis were conducted. Gene expression heatmaps were plotted. miRNAs regulating central DEGs were selected through TargetScan. A total of 626 DEGs were identified. According to gene ontology (GO) analysis, they were primarily enriched in small molecule metabolic processes, drug metabolic processes, binding of identical proteins, and lipid metabolic processes. Kyoto Encyclopedia of Gene and Genome (KEGG) analysis results indicated that the target genes were mainly enriched in metabolic pathways, phagosomes, glycine, serine, and threonine metabolism. The construction and analysis of the PPI network revealed 3 core genes (NDC80, CENPF, RRM2). Gene expression heatmaps showed that core genes (CENPF, NDC80) were highly expressed in HCC and cirrhosis samples. CTD analysis found that 2 genes (CENPF and NDC80) were associated with liver, jaundice, ascites, fever, dyspepsia, and hepatic encephalopathy. CENPF and NDC80 are highly expressed in HCC and cirrhosis, and CENPF and NDC80 might be the biomarkers of rehabilitation nursing of HCC and cirrhosis.

A comprehensive comparison of molecular and phenotypic profiles between hepatitis B virus (HBV)-infected and non-HBV-infected hepatocellular carcinoma by multi-omics analysis

Hepatitis B virus (HBV) infection is a major etiology of hepatocellular carcinoma (HCC). An interesting question is how different are the molecular and phenotypic profiles between HBV-infected (HBV+) and non-HBV-infected (HBV-) HCCs? Based on the publicly available multi-omics data for HCC, including bulk and single-cell data, and the data we collected and sequenced, we performed a comprehensive comparison of molecular and phenotypic features between HBV+ and HBV- HCCs. Our analysis showed that compared to HBV- HCCs, HBV+ HCCs had significantly better clinical outcomes, higher degree of genomic instability, higher enrichment of DNA repair and immune-related pathways, lower enrichment of stromal and oncogenic signaling pathways, and better response to immunotherapy. Furthermore, in vitro experiments confirmed that HBV+ HCCs had higher immunity, PD-L1 expression and activation of DNA damage response pathways. This study may provide insights into the profiles of HBV+ and HBV- HCCs, and guide rational therapeutic interventions for HCC patients.

Identification and Validation of Basement Membrane Related LncRNA Signatures as a Novel Prognostic Model for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a significant cancer with limited treatments and a poor prognosis, with the basement membrane (BM) playing a crucial role in its initiation and growth. This study utilized data from The Cancer Genome Atlas and the Gene Expression Omnibus (GEO) databases to identify basement membrane-related genes differentially expressed in HCC. Through gene co-expression analysis, BM-associated long non-coding RNAs (lncRNAs) were discovered. LncRNAs related to HCC survival were selected via univariate analysis, and a prognostic model was constructed using LASSO regression and multivariate analysis. This model effectively classified HCC patients into high and low-risk groups, uncovering significant differences in prognosis, immune response, mutation, and drug sensitivity. Six BM-related lncRNAs (GSEC, MIR4435-2HG, AC092614.1, AC127521.1, LINC02580, and AC008050.1) were validated in normal and HCC cell lines, and the key role of AC092614.1 in regulating proliferation, migration, and invasion of HCC cells in vitro was explored. This research emphasizes the prognostic and therapeutic relevance of BM-related lncRNAs in HCC, highlighting AC092614.1's role in disease progression and as a potential target for targeted therapy.

Clinical Application of Different Liquid Biopsy Components in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common form of primary liver cancer, usually occurring in the background of chronic liver disease. HCC lethality rate is in the third highest place in the world. Patients with HCC have concealed early symptoms and possess a high-level of heterogeneity. Once diagnosed, most of the tumors are in advanced stages and have a poor prognosis. The sensitivity and specificity of existing detection modalities and protocols are suboptimal. HCC calls for more sophisticated and individualized therapeutic regimens. Liquid biopsy is non-invasive, repeatable, unaffected by location, and can be monitored dynamically. It has emerged as a useable aid in achieving precision malignant tumor treatment. Circulating tumor cells (CTCs), circulating nucleic acids, exosomes and tumor-educated platelets are the commonest components of a liquid biopsy. It possesses the theoretical ability to conquer the high heterogeneity and the difficulty of early detection for HCC patients. In this review, we summarize the common enrichment techniques and the clinical applications in HCC for different liquid biopsy components. Tumor recurrence after HCC-related liver transplantation is more insidious and difficult to treat. The clinical use of liquid biopsy in HCC-related liver transplantation is also summarized in this review.

α-FAtE: A new predictive score of response to atezolizumab plus bevacizumab for unresectable hepatocellular carcinoma

Atezolizumab plus bevacizumab (AB) and lenvatinib can be alternatively used as first-line systemic treatment of unresectable hepatocellular carcinoma (HCC). However, no direct comparison of the two regimens has been performed in randomized clinical trials, making the identification of baseline differential predictors of response of major relevance to tailor the best therapeutic option to each patient. Baseline clinical and laboratory characteristics of real-world AB-treated HCC patients were analyzed in uni- and multivariate analyses to find potential prognostic factors of overall survival (OS). Significant variables were incorporated in a composite score (α-FAtE) and it was tested for specificity and sensitivity in receiver operating characteristic (ROC) curve and in multivariate analysis for OS. The score was applied in uni- and multivariate analyses for OS of a comparable lenvatinib-treated HCC population. Finally, comparison between treatments was performed in patients with low and high α-FAtE scores and predictivity estimated by interaction analysis. Time-to-progression (TTP) was a secondary endpoint. OS of AB-treated HCC patients was statistically longer in those with α-fetoprotein <400 ng/mL (HR 0.62, p = .0407), alkaline phosphatase (ALP) <125 IU/L (HR 0.52, p = .0189) and eosinophil count ≥70/μL (HR 0.46, p = .0013). The α-FAtE score was generated by the sum of single points attributed to each variable among the above reported. In ROC curve analysis, superior sensitivity and specificity were achieved by the score compared to individual variables (AUC 0.794, p < .02). Patients with high score had longer OS (HR 0.44, p = .0009) and TTP (HR 0.34, p < .0001) compared to low score if treated with AB, but not with lenvatinib. Overall, AB was superior to lenvatinib in high score patients (HR 0.55, p = .0043) and inferior in low score ones (HR 1.75, p = .0227). At interaction test, low α-FAtE score resulted as negative predictive factor of response to AB (p = .0004). In conclusion, α-FAtE is a novel prognostic and predictive score of response to first-line AB for HCC patients that, if validated in prospective studies, could drive therapeutic choice between lenvatinib and AB.

Kontrastmittelsonografie eines fibrolamellären hepatozellulären Karzinoms

Wir berichten über einen 24-jährigen Patienten, der sich mit anhaltenden Oberbauchschmerzen, Übelkeit und Völlegefühl ohne Erbrechen seit 5 Monaten zur ambulanten endoskopischen Diagnostik vorstellte. Bei der körperlichen Untersuchung fiel eine Verhärtung im Epigastrium ohne Druckschmerzhaftigkeit auf. Endoskopisch zeigte sich lediglich eine Impression des Bulbus duodeni bei intakter Duodenalschleimhaut. Darüber hinaus lagen unauffällige Befunde in Gastroskopie und Ileokoloskopie vor. Abdomensonografisch zeigte sich im linken Leberlappen eine große inhomogene Raumforderung mit scharfer, unregelmäßiger Begrenzung. Der rechte Leberlappen wies eine komplett unauffällige Sonomorphologie auf, insbesondere keine Zeichen des Parenchymschadens oder einer Leberzirrhose. Entlang der oberen mesenterialen Gefäße stellten sich mehrere vergrößerte Lymphknoten mit Kontakt zum Bulbus duodeni dar. In der Kontrastmittelsonografie (CE-US) zeigte die Leberläsion das typische Perfusionsmuster eines hepatozellulären Karzinoms. Zur Klärung des malignitätsverdächtigen Befunds wurde eine sonografisch gesteuerte Stanzbiopsie durchgeführt. Die histopathologische Aufarbeitung ergab den Befund eines hepatozellulären Karzinoms vom fibrolamellären Subtyp.

Mit diesem Fallbericht möchten wir zeigen, dass das HCC vom fibrolamellären Subtyp, trotz einer starken kollagenreichen bindegewebigen Stromakomponente in der Histopathologie, ein HCC-typisches Perfusionsmuster in der KM-Sonografie aufweist.

Comprehensive analysis on clinical significance and therapeutic targets of LDL receptor related protein 11 (LRP11) in liver hepatocellular carcinoma

LDL lipoprotein receptor-related protein 11 (LRP11) plays a role in several tumors. However, their roles in hepatocellular carcinoma remain unclear. The present study aimed to explore the expression profile and prognostic value of LRP11 in liver hepatocellular carcinoma (LIHC) patients using various cancer databases and bioinformatic tools. In bioinformatics analysis, The Cancer Genome Atlas datasets showed increased LRP11 expression in tumor tissues compared to that in non-tumor tissues in various cancers. Moreover, patients with high expression LRP11 correlated with poor prognosis and clinical features. The LRP11 expression positively correlated with the infiltration of immune cells such as macrophages, neutrophils, and myeloid-derived suppressor cells and a combination of high LRP11 expression and high immune infiltrates was associated with the worst survival in LIHC tumors. Our results also indicated that LRP11 expression was closely associated with immune-modulate function, such as antigen presentation. In DNA methylation profiling, hypomethylation of LRP11 is widely observed in tumors and has prognostic value in LIHC patients. Functional enrichment analysis revealed that LIHC-specific LRP11 interacting genes are involved in protein binding, intracellular processing, and G-protein-related signaling pathways. Analyses of drug sensitivity and immune checkpoint inhibitor predict a number of drugs that could potentially be used to target LRP11. In addition, in vitro experiments verified the promoting effect of LRP11 on the migration, invasion, and colony formation capacity of hepatocellular carcinoma cells. Collectively, our results aided a better understanding of the clinical significance of LRP11 in gene expression, functional interactions, and epigenetic regulation in LIHC and suggested that it may be a useful prognostic biomarker for LIHC patients.

A robust primary liver cancer subtype related to prognosis and drug response based on a multiple combined classifying strategy

The recurrence or resistance to treatment of primary liver cancer (PLL) is significantly related to the heterogeneity present within the tumor. In this study, we integrated prognosis risk score, mRNAsi index, and immune characteristics clustering to classify patients. The four subtypes obtained from the combined classification are associated with PLC's prognosis and drug response. In these subtypes, we observed mRNAsiH_ICCA subtype, the intersection between high mRNAsi and immune characteristics clustering A, had the worst prognosis. Specifically, immune characteristics clustering B (ICC_B) had high drug sensitivity in most drugs regardless of the value of mRNAsi. On the other hand, patients with low mRNAsi responded better to ten drugs including KU-55933 and NU7441, while patients with high mRNAsi might benefit from drugs like Leflunomide. By matching the specific characteristics of each combined subtype with the drug-induced cell line expression profile, we identified a group of potential therapeutic drugs that might regulate the expression of disease signature genes. We developed a feasible multiple combined typing strategy, hoping to guide therapeutic selection and promote the development of precision medicine.

A novel nomogram to predict the overall survival of early-stage hepatocellular carcinoma patients following ablation therapy

Introduction

This study aimed to assess factors affecting the prognosis of early-stage hepatocellular carcinoma (HCC) patients undergoing ablation therapy and create a nomogram for predicting their 3-, 5-, and 8-year overall survival (OS).

Methods

The research included 881 early-stage HCC patients treated at Beijing You'an Hospital, affiliated with Capital Medical University, from 2014 to 2022. A nomogram was developed using independent prognostic factors identified by Lasso and multivariate Cox regression analyses. Its predictive performance was evaluated with concordance index (C-index), receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).

Results

The study identified age, tumor number, tumor size, gamma-glutamyl transpeptidase (GGT), international normalized ratio (INR), and prealbumin (Palb) as independent prognostic risk factors. The nomogram achieved C-indices of 0.683 (primary cohort) and 0.652 (validation cohort), with Area Under the Curve (AUC) values of 0.776, 0.779, and 0.822 (3-year, 5-year, and 8-year OS, primary cohort) and 0.658, 0.724, and 0.792 (validation cohort), indicating that the nomogram possessed strong discriminative ability. Calibration and DCA curves further confirmed the nomogram's predictive accuracy and clinical utility. The nomogram can effectively stratify patients into low-, intermediate-, and high-risk groups, particularly identifying high-risk patients.

Conclusions

The established nomogram in our study can provide precise prognostic information for HCC patients following ablation treatment and enable physicians to accurately identify high-risk individuals and facilitate timely intervention.

Mechanistically based blood proteomic markers in the TGF-β pathway stratify risk of hepatocellular cancer in patients with cirrhosis

Hepatocellular carcinoma (HCC) is the third leading cause of death from cancer worldwide but is often diagnosed at an advanced incurable stage. Yet, despite the urgent need for blood-based biomarkers for early detection, few studies capture ongoing biology to identify risk-stratifying biomarkers. We address this gap using the TGF-β pathway because of its biological role in liver disease and cancer, established through rigorous animal models and human studies. Using machine learning methods with blood levels of 108 proteomic markers in the TGF-β family, we found a pattern that differentiates HCC from non-HCC in a cohort of 216 patients with cirrhosis, which we refer to as TGF-β based Protein Markers for Early Detection of HCC (TPEARLE) comprising 31 markers. Notably, 20 of the patients with cirrhosis alone presented an HCC-like pattern, suggesting that they may be a group with as yet undetected HCC or at high risk for developing HCC. In addition, we found two other biologically relevant markers, Myostatin and Pyruvate Kinase M2 (PKM2), which were significantly associated with HCC. We tested these for risk stratification of HCC in multivariable models adjusted for demographic and clinical variables, as well as batch and site. These markers reflect ongoing biology in the liver. They potentially indicate the presence of HCC early in its evolution and before it is manifest as a detectable lesion, thereby providing a set of markers that may be able to stratify risk for HCC.

Liquid-liquid phase separation-related lncRNA prognostic signature and ZNF32-AS2 as a novel biomarker in hepatocellular carcinoma

BACKGROUND

Liquid-liquid phase separation (LLPS) enhances oncogenic signaling pathways and advances cancer progression, and has been proposed as a promising cancer biomarker and intervention target. Nevertheless, doubts remain about the prognostic importance of LLPS-related long non-coding RNAs (lncRNAs) in hepatocellular carcinoma (HCC).

METHODS

An LLPS-related lncRNA prognostic signature was generated by drivers and regulators of LLPS, and was validated in external datasets. The underlying genetic changes and functional enrichment of the signature were assessed. The drug sensitivity and response to immunotherapy were predicted in patients categorized as high-risk and low-risk. Clinical samples, phase separation agonist, and dispersant were used to identify lncRNAs with the most significant expression change. Cancer cells with ZNF32-AS2 expression regulation were subjected to colony formation assay, scratch test assay, migration and invasion assay, sorafenib resistance assay, and xenograft tumor model.

RESULTS

The signature of LLPS-related hub lncRNAs identified through Weighted Gene Co-Expression Network Analysis showed outstanding performance in training and external validation cohorts consistently, and the molecular characteristics varied between different risk groups. Potential drugs for high-risk individuals were identified, and low-risk individuals demonstrated a more favorable reaction to immunotherapy. ZNF32-AS2 showed the most significant expression change in phase separation agonist and dispersant treatment. ZNF32-AS2 promoted the proliferation, mobility, and sorafenib resistance of liver cancer cells.

CONCLUSIONS

The LLPS-related lncRNA signature may help assess prognosis and predict treatment efficacy in clinical settings. LLPS-related ZNF32-AS2 promoted the proliferation, mobility, and sorafenib resistance of liver cancer cells, and may be a novel potential biomarker in hepatocellular carcinoma.

Design, synthesis and biological evaluation of the positional isomers of the galactose conjugates able to target hepatocellular carcinoma cells via ASGPR-mediated cellular uptake and cytotoxicity

Galactose as a recognizing motif for asialoglycoprotein receptor (ASGPR) is a widely accepted vector to deliver cytotoxic agents in the therapy of hepatocellular carcinoma (HCC), however, the individual hydroxyl group of galactose (Gal) contributed to recognizing ASGPR is obscure and remains largely unanswered in the design of glycoconjugates. Herein, we designed and synthesized five positional isomers of Gal-anthocyanin Cy5.0 conjugates and three Gal-doxorubicin (Dox) isomers, respectively. The fluorescence intensity of Gal-Cy5.0 conjugates accumulated in cancer cells hinted the optimal modification sites of positions C2 and C6. Comparing to the cytotoxicity of other conjugates, C2-Gal-Dox (11) was the most potent. Moreover, Gal-Dox conjugates significantly the toxicity of Dox. A progressively lower internalization capacity and siRNA technology implied the cellular uptake and cytotoxicity directly related to the ASGPR expression level. Accordingly, position C2 of galactose may be the best substitution site via ASGPR mediation in the design of anti-HCC glycoconjugates.

Immunomodulation of cuproptosis and ferroptosis in liver cancer

According to statistics, the incidence of liver cancer is increasing yearly, and effective treatment of liver cancer is imminent. For early liver cancer, resection surgery is currently the most effective treatment. However, resection does not treat the disease in advanced patients, so finding a method with a better prognosis is necessary. In recent years, ferroptosis and cuproptosis have been gradually defined, and related studies have proved that they show excellent results in the therapy of liver cancer. Cuproptosis is a new form of cell death, and the use of cuproptosis combined with ferroptosis to inhibit the production of hepatocellular carcinoma cells has good development prospects and is worthy of in-depth discussion by researchers. In this review, we summarize the research progress on cuproptosis combined with ferroptosis in treating liver cancer, analyze the value of cuproptosis and ferroptosis in the immune of liver cancer, and propose potential pathways in oncotherapy with the combination of cuproptosis and ferroptosis, which can provide background knowledge for subsequent related research.

Biomarker Identification in Liver Cancers Using Desorption Electrospray Ionization Mass Spectrometry (DESI-MS) Imaging: An Approach for Spatially Resolved Metabolomics

Liver cancers are characterized by interindividual and intratumoral heterogeneity, which makes early diagnosis and the development of therapies challenging. Desorption electrospray ionization mass spectrometry (DESI-MS) imaging is a potent and sensitive MS ionization technique for direct, unaltered 2D and 3D imaging of metabolites in complex biological samples. Indeed, DESI gently desorbs and ionizes analyte molecules from the sample surface using an electrospray source of highly charged aqueous spray droplets in ambient conditions. DESI-MS imaging of biological samples allows untargeted analysis and characterization of metabolites in liver cancers to identify new biomarkers of malignancy. In this chapter, we described a detailed protocol using liver cancer samples collected and stored for histopathology examination, either as frozen or as formalin-fixed, paraffin-embedded specimens. Such hepatocellular carcinoma samples can be subjected to DESI-MS analyses, illustrating the capacity of spatially resolved metabolomics to distinguish malignant lesions from adjacent normal liver tissue.

[Contrast-Enhanced Ultrasound of Fibrolamellar Hepatocellular Carcinoma]

We present the case of a 24-year-old male patient, who was admitted for endoscopy due to sustained pain in the upper abdomen with nausea and postprandial fullness without vomiting for more than 5 months. In the physical examination, an epigastric induration was found. Endoscopy revealed an external impression of the proximal duodenum. Beyond that, normal findings could be ascertained in gastroscopy and ileo-colonoscopy. Abdominal ultrasound identified a large hypoechoic lesion in the left liver lobe with a sharp delineation. Along the upper mesenteric vessels, enlarged lymphnodes were visible with contact to the proximal duodenum. Contrast-enhanced ultrasound (CE-US) was conducted and revealed the typical perfusion pattern of hepatocellular carcinoma. For further assessment, an ultrasound-guided core-biopsy of the lesion was performed. The histopathological evaluations resulted in the diagnosis of a hepatocellular carcinoma of fibrolamellar subtype.With the present case, we want to illustrate the perfusion pattern of a fibrolamellar hepatocellular carcinoma in contrast-enhanced ultrasound. Even though the tumor tissue is surrounded by lamellar bands of fibrosis with collagen-rich fibers, the perfusion pattern is consistent with the previously known appearance of HCC in CE-US.

Establishment and validation of a novel lysosome-related gene signature for predicting prognosis and immune landscape in hepatocellular carcinoma

BACKGROUND

Recent studies have shown that lysosomes not only provide energy for tumor cell growth, but also participate in the occurrence and development of malignant tumors by regulating various ways of tumor cell death. However, the role of lysosome associated genes (LSAGs) in hepatocellular carcinoma (HCC) remains unclear.

METHODS

Transcriptome data and clinical data of HCC were downloaded from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. We identified differential expression of LSAGs by comparing tumor tissue with normal liver tissue. Subsequently, we used univariate COX analysis and least absolute shrinkage and selection operator (LASSO) COX regression to construct the prognostic feature of LSAGs. Kaplan-Meier survival curve and receiver operating characteristic curve were used to evaluate the predictive ability of LSAGs feature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for functional enrichment analysis of risk differential genes. The relationship between LSAGs score and tumor microenvironment and chemotherapy drug sensitivity was analyzed. Finally, the cellular communication of tumor cells with high and low expression of model LSAGs was explored.

RESULTS

We identified sixteen prognostic associated LSAGs, four of which were selected to construct prognostic feature of LSAGs. Patients in the low LSAGs group had a better prognosis than those in the high LSAGs group. GO and KEGG analyses showed that risk differential genes were enriched in leukocyte migration, cytokine-cytokine receptor interaction and PI3K-Akt signaling pathway. The group with low LSAGs score had lower immune score. Patients in the high LSAGs group were more sensitive to drugs for chemotherapy. In addition, tumor cells with high expression of model LSAGs showed stronger association with immune cells through the interleukin-2 (IL2), fibroblast growth factor (FGF), adiponectin, and bone morphogenetic proteins (BMP) signaling pathways.

CONCLUSION

We established a LSAGs signature that had the ability to predict clinical prognosis and immune landscape, proposing potential therapeutic targets for HCC.

Comprehensive clinicopathological significance and putative transcriptional mechanisms of Forkhead box M1 factor in hepatocellular carcinoma

BACKGROUND

The Forkhead box M1 factor (FOXM1) is a crucial activator for cancer cell proliferation. While FOXM1 has been shown to promote hepatocellular carcinoma (HCC) progression, its transcriptional mechanisms remain incompletely understood.

METHODS

We performed an in-house tissue microarray on 313 HCC and 37 non-HCC tissue samples, followed by immunohistochemical staining. Gene chips and high throughput sequencing data were used to assess FOXM1 expression and prognosis. To identify candidate targets of FOXM1, we comprehensively reanalyzed 41 chromatin immunoprecipitation followed by sequencing (ChIP-seq) data sets. We predicted FOXM1 transcriptional targets in HCC by intersecting candidate FOXM1 targets with HCC overexpressed genes and FOXM1 correlation genes. Enrichment analysis was employed to address the potential mechanisms of FOXM1 underlying HCC. Finally, single-cell RNA sequencing analysis was performed to confirm the transcriptional activity of FOXM1 on its predicted targets.

RESULTS

This study, based on 4235 HCC tissue samples and 3461 non-HCC tissue samples, confirmed the upregulation of FOXM1 in HCC at mRNA and protein levels (standardized mean difference = 1.70 [1.42, 1.98]), making it the largest multi-centered study to do so. Among HCC patients, FOXM1 was increased in Asian and advanced subgroups, and high expression of FOXM1 had a strong ability to differentiate HCC tissue from non-HCC tissue (area under the curve = 0.94, sensitivity = 88.72%, specificity = 87.24%). FOXM1 was also shown to be an independent exposure risk factor for HCC, with a pooled hazard ratio of 2.00 [1.77, 2.26]. The predicted transcriptional targets of FOXM1 in HCC were predominantly enriched in nuclear division, chromosomal region, and catalytic activity acting on DNA. A gene cluster encoding nine transcriptional factors was predicted to be positively regulated by FOXM1, promoting the cell cycle signaling pathway in HCC. Finally, the transcriptional activity of FOXM1 and its targets was supported by single-cell analysis of HCC cells.

CONCLUSIONS

This study not only confirmed the upregulation of FOXM1 in HCC but also identified it as an independent risk factor. Moreover, our findings enriched our understanding of the complex transcriptional mechanisms underlying HCC pathogenesis, with FOXM1 potentially promoting HCC progression by activating other transcription factors within the cell cycle pathway.