Cancer stem cells (CSCs) constitute a small yet crucial subgroup in tumors, known for their capacity to self-renew, differentiate, and promote tumor growth, metastasis, and resistance to therapy. These characteristics position CSCs as significant factors in tumor recurrence and unfavorable clinical results, emphasizing their role as targets for therapy. Autophagy, an evolutionarily preserved cellular mechanism for degradation and recycling, has a complex function in cancer by aiding cell survival during stress and preserving balance by eliminating damaged organelles and proteins. Although autophagy can hinder tumor growth by reducing genomic instability, it also aids tumor advancement, particularly in harsh microenvironments, highlighting its dual characteristics. Recent research has highlighted the complex interactions between autophagy and CSCs, showing that autophagy governs CSC maintenance, boosts survival, and aids in resistance to chemotherapy and radiotherapy. On the other hand, in specific situations, autophagy may restrict CSC growth by increasing differentiation or inducing cell death. These intricate interactions offer both obstacles and possibilities for therapeutic intervention. Pharmacological modulation of autophagy, via inhibitors like chloroquine or by enhancing autophagy when advantageous, has demonstrated potential in making CSCs more responsive to standard treatments. Nonetheless, applying these strategies in clinical settings necessitates a better understanding of context-dependent autophagy dynamics and the discovery of dependable biomarkers indicating autophagic activity in CSCs. Progressing in this area might unveil novel, accurate strategies to tackle therapy resistance, lessen tumor recurrence, and ultimately enhance patient outcomes.

Lymph node metastasis (LNM) is strongly associated with poor prognosis in hypopharyngeal squamous carcinoma (HPSCC). Identifying key drivers of LNM and potential therapeutic targets in HPSCC is therefore essential for the early detection of high-risk patients and for informing personalized treatment strategies.

Single-cell RNA sequencing data were used to characterize malignant epithelial cells (maECs) in HPSCC primary tumors (PT) and LNM, as well as differences in cell-to-cell communication. Concurrently, combined with bulk RNA sequencing data, a ligand receptor pairs (LRs) model was developed to predict the prognosis of HPSCC patients.

PT and LNM maECs have different gene expression characteristics, with genes involved in interferon signaling and TGF-β response pathways enriched in LNM maECs, suggesting potential immunosuppressive reprogramming. Cell communication analysis revealed distinct interactions and signaling features in PT and LNM microenvironments. Subsequently, a 4-LRs model was constructed to stratify HPSCC patients into low-or high-risk groups, with the high-risk group demonstrating significantly worse overall survival (OS) outcomes compared with the low-risk group in the training (p < 0.0001), testing (p = 0.0021), and entire (p < 0.0001) cohorts. Receiver operating characteristic curves showed that this risk model can effectively predict the 1-, 3-, and 5-year OS of HPSCC patients. Notably, the risk score effectively discriminated LNM status (area under the curve [AUC] = 0.927) among HPSCC patients, highlighting its potential as a HPSCC metastasis prediction tool.

These results provide biomarkers of LNM maECs as well as potential mechanisms of HPSCC metastasis, which may help with the precision treatment, diagnosis, and prognosis of HPSCC.

Cancer stem cells (CSCs) are well-established drivers of tumorigenesis, but their role in regulating tumor metastasis remains poorly understood. Here, we report the identification and characterization of a cluster of metastasis-promoting CSC-like cells in hepatocellular carcinoma (HCC).

CSC-like cells in HCC were identified through the analysis of single cell RNA-sequencing data from 19 HCC samples. The stemness and invasive characteristics of these cells were evaluated using bioinformatical analyses of nine clinical cohorts and experimental validations. Spatial transcriptomics sequencing of 12 HCC samples revealed the cellular interactions between the CSC-like cells and tumor microenvironments, which were validated through gene co-expression analyses and immunohistochemistry. Finally, signaling pathway blockade was used to assess the potential clinical application of CSC-like cells.

Through comprehensive analyses of single cell RNA-sequencing data from 19 patients with HCC and spatial transcriptomics data from 12 patients with HCC, a metastasis-promoting CSC-like subpopulation was identified. These CSC-like cells expressed high levels of epithelial-mesenchymal transition genes and were associated with poor prognosis of HCC. Histologically, CSC-like cells were enriched in highly aggressive tumors, especially in intrahepatic disseminated foci, where they interacted with immune cells. Functionally, CSC-like cells induced macrophage M2 polarization and T cell exhaustion through the ICAM1 signaling pathway, forming immunosuppressive microenvironments. Downregulation of ICAM1 expression in CSC-like cells suppressed macrophage M2-polarization and T cell exhaustion, thereby reversing antitumor immune effects.

Our study identified a metastasis-promoting CSC subpopulation, providing a potential perspective for CSC-targeted therapies in HCC.

The heterogeneity of CSCs in HCC has been identified, yet the identification and characterization of metastasis-promoting CSC subpopulations remain unexplored. Here, we identified a CSC-like tumor cell subpopulation that promotes HCC metastasis by increasing cell invasiveness and suppressing antitumor immune responses via the ICAM1 signaling pathway. Our study uncovers novel mechanisms of HCC metastasis from the perspective of CSCs, and proposes potential tumor therapeutic strategies by inhibiting cellular interactions between CSC-like cells and immune cells.

Cancer is one of the most fatal diseases threatening public health globally, and tumor metastasis causes greater than 90 % of cancer-associated deaths, presenting huge challenges for detection and efficient treatment of various human cancers. Cancer stem cells (CSCs) are a rare population of cancer cells and increasing evidences indicated CSCs are the driving force of tumor metastasis. In this study, a p-AuNSs-assisted single-cell Raman spectra has been established, to extract and amplify of CSCs fingerprints with single cell sensitivity. The gathered rich molecular information was further assigned according to the characteristic Raman peaks, and the results revealed a huge difference in the expression of molecules between CSCs and cancer cells, such as nucleic acids, proteins, saccharides and lipids. Furthermore, multiple data analysis algorithms including PCA, SVM, RF and KNN, were employed to reveal the fundamental characteristics and classification of CSCs and cancer cells based on the whole p-AuNSs-assisted single-cell Raman spectra. This work is beneficial for not only providing deep insights for molecular behaviors of tumor metastasis based on CSCs, but also could obtain significant information to aid medical diagnosis and to design effective CSCs-based therapeutic intervention clinically.

Hepatocellular carcinoma (HCC) has limited therapeutic options and a poor prognosis. The endoplasmic reticulum (ER) plays a crucial role in tumor progression and response to stress, making it a promising target for HCC stratification. This study aimed to develop a risk stratification model using ER stress-related signatures.

We utilized transcriptome data from The Cancer Genome Atlas and Gene Expression Omnibus, which encompass whole-genome expression profiles and clinical annotations. Machine learning algorithms, including the least absolute shrinkage and selection operator, random forest, and support vector machine recursive feature elimination, were applied to the key genes associated with HCC prognosis. A prognostic system was developed using univariate Cox hazard analysis and least absolute shrinkage and selection operator Cox regression, followed by validation using Kaplan-Meier analysis and receiver operating characteristic curves. Tumor immune dysfunction and exclusion tools were used to predict immunotherapy responsiveness.

Two distinct clusters associated with ER stress were identified in HCC, each exhibiting unique clinical and biological features. Using a computational approach, a prognostic risk model, namely the ER stress-related signature, was formulated, demonstrating enhanced predictive accuracy compared with that of existing prognostic models. An effective clinical nomogram was established by integrating the risk model with clinicopathological factors. Patients with lower risk scores exhibited improved responsiveness to various chemotherapeutic, targeted, and immunotherapeutic agents.

The critical role of ER stress in HCC is highlighted. The ER stress-related signature developed in this study is a powerful tool to assess the risk and clinical treatment of HCC.

Spatial cellular context is crucial in shaping intratumor heterogeneity. However, understanding how each tumor establishes its unique spatial landscape and what factors drive the landscape for tumor fitness remains significantly challenging. Here, we analyzed over 2 million cells from 50 tumor biospecimens using spatial single-cell imaging and single-cell RNA sequencing. We developed a deep learning-based strategy to spatially map tumor cell states and the architecture surrounding them, which we referred to as Spatial Dynamics Network (SDN). We found that different tumor cell states may be organized into distinct clusters, or 'villages', each supported by unique SDNs. Notably, tumor cell villages exhibited village-specific molecular co-dependencies between tumor cells and their microenvironment and were associated with patient outcomes. Perturbation of molecular co-dependencies via random spatial shuffling of the microenvironment resulted in destabilization of the corresponding villages. This study provides new insights into understanding tumor spatial landscape and its impact on tumor aggressiveness.

Liver cancer poses a global health challenge with limited therapeutic options. Notably, the limited success of current therapies in patients with primary liver cancers (PLCs) may be attributed to the high heterogeneity of both hepatocellular carcinoma (HCCs) and intrahepatic cholangiocarcinoma (iCCAs). This heterogeneity evolves over time as tumor-initiating stem cells, or cancer stem cells (CSCs), undergo (epi)genetic alterations or encounter microenvironmental changes within the tumor microenvironment. These modifications enable CSCs to exhibit plasticity, differentiating into various resistant tumor cell types. Addressing this challenge requires urgent efforts to develop personalized treatments guided by biomarkers, with a specific focus on targeting CSCs. The lack of effective precision treatments for PLCs is partly due to the scarcity of ex vivo preclinical models that accurately capture the complexity of CSC-related tumors and can predict therapeutic responses. Fortunately, recent advancements in the establishment of patient-derived liver cancer cell lines and organoids have opened new avenues for precision medicine research. Notably, patient-derived organoid (PDO) cultures have demonstrated self-assembly and self-renewal capabilities, retaining essential characteristics of their respective in vivo tissues, including both inter- and intratumoral heterogeneities. The emergence of PDOs derived from PLCs serves as patient avatars, enabling preclinical investigations for patient stratification, screening of anticancer drugs, efficacy testing, and thereby advancing the field of precision medicine. This review offers a comprehensive summary of the advancements in constructing PLC-derived PDO models. Emphasis is placed on the role of CSCs, which not only contribute significantly to the establishment of PDO cultures but also faithfully capture tumor heterogeneity and the ensuing development of therapy resistance. The exploration of PDOs' benefits in personalized medicine research is undertaken, including a discussion of their limitations, particularly in terms of culture conditions, reproducibility, and scalability.

Pyroptosis has been recently identified as a hallmark of cancer biology; however, the potential of pyroptosis-related genes (PRGs) as prognostic markers has not been fully elucidated in hepatocellular carcinoma (HCC). The aim of this study was to develop a PRG-associated risk signature for prediction prognosis in patients with HCC.

We identified 35 PRGs from the published literature, and pyroptosis subtypes were identified through bioinformatics methods. The risk score model was established by applying least absolute shrinkage and selection operator (LASSO) Cox regression method in The Cancer Genome Atlas (TCGA) cohort and validated in International Cancer Genome Consortium (ICGC) datasets. Additionally, immune infiltration, enriched pathways, and genomic alterations were compared between the high- and low-risk score subgroups. Finally, a nomogram containing the pyroptosis risk score and other prognosis-related clinical factors was developed for predicting the overall survival of patients with HCC.

Based on the expression profile of PRGs, we determined two pyroptosis-related subtypes (cluster A and cluster B) of HCC associated with different immune characteristics and significantly different prognoses. The risk score model showed that upregulation of GPX4, CASP8, NOD2, and GSDME was associated with poor overall survival (OS), while high expression of NLRP6 was associated with good prognosis. Compared with group with a lower risk score, the group with a high risk score had worse prognosis (P<0.001) and a high level of immune cell infiltration. Functional analysis indicated that the highly expressed genes in the high-risk group were mainly enriched in various signaling pathways, while the genes with low expression in the high-risk group were mainly enriched in different biochemical metabolic translations. Genomic alterations in high-risk and low-risk populations suggested that mutations in the TP53 gene are highly associated with pyroptosis in patients with HCC. A nomogram including risk score and TNM stage demonstrated good prognostic ability in predicting 1-year, 3-year, and 5-year OS.

We developed and verified a prognostic risk model based on PRGs for patients with HCC, which may provide a robust tool for predicting outcomes in this setting.

Macrophages, as the predominant phagocytes, play an essential role in pathogens defense and tissue homeostasis maintenance. In the context of cancer, tumor-associated macrophages (TAMs) have evolved into cunning actors involved in angiogenesis, cancer cell proliferation and metastasis, as well as the construction of immunosuppressive microenvironment. Once properly activated, macrophages can kill tumor cells directly through phagocytosis or attack tumor cells indirectly by stimulating innate and adaptive immunity. Thus, the prospect of targeting TAMs has sparked significant interest and emerged as a promising strategy in immunotherapy. In this review, we summarize the diverse roles and underlying mechanisms of TAMs in cancer development and immunity and highlight the TAM-based therapeutic strategies such as inhibiting macrophage recruitment, inhibiting the differentiation reprogramming of TAMs, blocking phagocytotic checkpoints, inducing trained macrophages, as well as the potential of engineered CAR-armed macrophages in cancer therapy.

Cancer stem cells (CSCs) play a central role in cancer progression, therapy resistance, and disease recurrence. With the use of a quadruple-mutant mouse intestinal cancer organoid model and single-cell RNA-sequencing analysis, we have now identified glycosylphosphatidylinositol-specific phospholipase D1 (GPLD1), an enzyme that catalyzes the cleavage of glycosylphosphatidylinositol (GPI) anchors of membrane proteins, as a marker of slowly cycling CSCs. Ablation of Gpld1+ cells in combination with 5-fluorouracil treatment greatly attenuated cell viability in and regrowth of the intestinal cancer organoids. In addition, we identified serine protease 8 (PRSS8) as a key substrate of GPLD1 in human colorectal cancer cells. GPLD1 cleaves the GPI anchor of PRSS8 and thereby mediates release of the protease from the plasma membrane, resulting in the activation of Wnt signalling and promotion of the epithelial-mesenchymal transition (EMT) in the cancer cells. Pharmacological inhibition of GPLD1 suppressed Wnt signalling activity and EMT in association with upregulation of the amount of functional PRSS8 at the plasma membrane. Our findings suggest that targeting of GPLD1 in colorectal cancer might contribute to a new therapeutic strategy that is based on suppression of Wnt signalling and EMT-related cancer progression driven by CSCs.

Personalized medicine is an emerging field that provides novel approaches to disease's early diagnosis, prevention, treatment, and prognosis based on the patient's criteria in gene expression, environmental factors, lifestyle, and diet. To date, hepatocellular carcinoma (HCC) is a significant global health burden, with an increasing incidence and significant death rates, despite advancements in surveillance, diagnosis, and therapeutic approaches. The majority of HCC lesions develop in patients with liver cirrhosis, carrying the risks of mortality associated with both the tumor burden and the cirrhosis. New therapeutic agents involving immune checkpoint inhibitors and targeted agents have been developed for sequential or concomitant application for advanced HCC but only a tiny percentage of patients benefit from each approach. Moreover, clinicians encounter difficulties determining the most appropriate regimen for each patient. This emphasizes the need for a personalized treatment approach. In other words, patients should no longer undergo treatment based on their tumor's histology but depending on the distinct molecular targets specific to their tumor biology. However, the utilization of precision medicine in managing HCC is still challenging. This review aims to discuss the role of personalized medicine in diagnosing, managing, and defining the prognosis of HCC. We also discuss the role of liquid biopsy and their clinical applications for immunotherapies in HCC. More clinical studies are still necessary to improve the precision of biomarkers used in the treatment decision for patients with HCC.

The gene F-box only protein 22 (FBXO22) has been discovered to promote the development of liver cancer tumors. Nevertheless, there remains considerable ambiguity regarding the involvement of FBXO22 in the processes of angiogenesis and metastasis in hepatocellular carcinoma (HCC). Our study has confirmed a significant upregulation of FBXO22 expression in both HCC samples and cellular models. The increased level of FBXO22 correlates strongly with the number of tumors, presence of vascular invasion, and poor prognosis. Experimental investigations have shown that FBXO22 significantly enhances angiogenesis and metastasis of HCC both in vitro and in vivo. Mechanistically, FBXO22 interacts with and ubiquitinates 40S ribosomal protein S5 (RPS5) on Lys85, thereby promoting its K48-linked ubiquitin-mediated degradation in the cytoplasm. Following a decrease in the expression of RPS5, activation of downstream PI3K/AKT signaling pathway occurs, leading to elevated levels of HIF-1α and vascular endothelial growth factor A (VEGF-A). Our study has shown that FBXO22 facilitates HCC angiogenesis and metastasis via the RPS5/AKT/HIF-1α/VEGF-A signaling axis. Notably, inhibition of FBXO22 enhances the efficacy of Lenvatinib both in vitro and in vivo. Therefore, FBXO22 may present itself as a potential target for therapeutic intervention in the treatment of HCC.

Cancer stem cells (CSCs) play a central role in tumor progression, recurrence, and resistance to conventional therapies, making them a critical focus in oncology research. This review provides a comprehensive analysis of CSC biology, emphasizing their self-renewal, differentiation, and dynamic interactions with the tumor microenvironment (TME). Key signaling pathways, including Wnt, Notch, and Hedgehog, are discussed in detail to highlight their potential as therapeutic targets. Current methodologies for isolating CSCs are critically examined, addressing their advantages and limitations in advancing precision medicine. Emerging technologies, such as CRISPR/Cas9 and single-cell sequencing, are explored for their transformative potential in unraveling CSC heterogeneity and informing therapeutic strategies. The review also underscores the pivotal role of the TME in supporting CSC survival, promoting metastasis, and contributing to therapeutic resistance. Challenges arising from CSC-driven tumor heterogeneity and dormancy are analyzed, along with strategies to mitigate these barriers, including novel therapeutics and targeted approaches. Ethical considerations and the integration of artificial intelligence in designing CSC-specific therapies are discussed as essential elements of future research. The manuscript advocates for a multi-disciplinary approach that combines innovative technologies, advanced therapeutics, and collaborative research to address the complexities of CSCs. By bridging existing gaps in knowledge and fostering advancements in personalized medicine, this review aims to guide the development of more effective cancer treatment strategies, ultimately improving patient outcomes.

Tumor-associated macrophages (TAMs) in the tumor microenvironment (TME) widely participate in the malignant progression in cancer. Previously, we have demonstrated that M1-like TAMs cascaded a stem-like phenotype of oral squamous cell carcinoma (OSCC). Yet, the underlying mechanisms still need to be demonstrated for the regulation of TAMs on cancer stem cells (CSCs) in OSCC. In this study, we investigated a group of CSCs with increased expression of cluster differentiation 10 (CD10), which acted as a mediator in the interaction network between TAMs and tumor-associated neutrophils (TANs) in OSCC. The results showed a significant association between TAMs infiltrations and increased expression of CD10 among all the CSCs-related molecules in OSCC. Then, we validated that OSCC cells with high CD10 expression possessed increased CSCs characteristics. TAMs could drive the heterogenetic CD10High CSCs by activating the IL6/STAT3/CD10 pathway. Furthermore, CD10High CSCs could recruit and reprogram tumor-associated neutrophils (TANs) in an immunosuppressive state by secreting S100A8/A9 in OSCC. These finding indicated that CD10High CSCs played great roles in signaling crosstalk between TAMs and TANs in OSCC, by which infiltrated TAMs drive CD 10High CSCs to recruit and reprogram TANs in an immunosuppressive state. Herein, we managed to demonstrate that TAMs could directly regulate a heterogenetic cluster of CSCs with high CD10 expression, and CD10High CSCs could recruit and reprogram TANs in OSCC. The novel crosstalk among OSCC-TAMs-CD10High CSCs-TANs might bring new prospects for improving the treatment strategies for OSCC patients.

Tumor heterogeneity is the substrate for tumor evolution and the linchpin of treatment resistance. Cancer cell heterogeneity is largely attributed to distinct genetic changes within each cell population. However, the widespread epigenome repatterning that characterizes most cancers is also highly heterogenous within tumors and could generate cells with diverse identities and malignant features. We show that high levels of the epigenetic regulator and oncogene, UHRF1, in zebrafish hepatocytes rapidly induced methylome disordering, loss of heterochromatin, and DNA damage, resulting in cell cycle arrest, senescence, and acquisition of stemness. Reducing UHRF1 expression transitions these cells from senescent to proliferation-competent. The expansion of these damaged cells results in hepatocellular carcinomas (HCC) that have immature cancer cells intermingled with fibroblasts, immune and senescent cells expressing high UHRF1 levels, which serve as reservoirs for new cancer cells. This defines a distinct and heterogenous HCC subtype resulting from epigenetic changes, stemness and senescence escape.

Single-cell RNA sequencing (scRNA-seq), which profiles gene expression at the cellular level, has effectively explored cell heterogeneity and reconstructed developmental trajectories. With the increasing research on diseases and biological processes, scRNA-seq datasets are accumulating rapidly, highlighting the urgent need for collecting and processing these data to support comprehensive and effective annotation and analysis. Here, we have developed a comprehensive Single-Cell transcriptome integration database for human and mouse (SCInter, https://bio.liclab.net/SCInter/index.php), which aims to provide a manually curated database that supports the provision of gene expression profiles across various cell types at the sample level. The current version of SCInter includes 115 integrated datasets and 1016 samples, covering nearly 150 tissues/cell lines. It contains 8016,646 cell markers in 457 identified cell types. SCInter enabled comprehensive analysis of cataloged single-cell data encompassing quality control (QC), clustering, cell markers, multi-method cell type automatic annotation, predicting cell differentiation trajectories and so on. At the same time, SCInter provided a user-friendly interface to query, browse, analyze and visualize each integrated dataset and single cell sample, along with comprehensive QC reports and processing results. It will facilitate the identification of cell type in different cell subpopulations and explore developmental trajectories, enhancing the study of cell heterogeneity in the fields of immunology and oncology.

Hepatocellular carcinoma (HCC) is a common type of cancer worldwide and ranks as the fourth leading cause of cancer-related deaths. This research investigation identified an upregulation of BAI1-associated protein 2-like 2 (BAIAP2L2) in HCC tissues, which was found to be an independent prognostic factor for overall survival in HCC patients. BAIAP2L2 was observed to enhance cell proliferation, metastasis, stemness, cell cycle progression, and inhibit apoptosis in HCC. Mechanistically, NFκB1 was found to stimulate BAIAP2L2 transcription by directly binding to its promoter region. BAIAP2L2 interacts with GABPB1 to inhibit its ubiquitin-mediated degradation and promote its nuclear translocation. BAIAP2L2 inhibits the levels of reactive oxygen species (ROS) by regulating GABPB1, thereby promoting cancer properties in HCC and reducing the sensitivity of HCC to lenvatinib. In summary, this study elucidates the role and underlying mechanism of BAIAP2L2 in HCC, providing a potential biomarker and therapeutic target for this disease.

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.

Oncolytic virotherapy has shown efficacy in various animal models and a few human cancers. However, there are still significant limitations for the implementation of these therapies. One such limitation is the emergence of cellular resistances, which may appear rapidly considering the high genetic heterogeneity of most tumors. We previously showed that cellular resistance to an oncolytic virus can be mediated by the chronic activation of innate immunity. Here, we explored the existence of additional resistance mechanisms in murine colon cancer-derived cells. For this purpose, we isolated two cellular clones that were resistant to the oncolytic virus VSV-D51. While one of the clones showed a strong resistance profile associated with increased cytokine-mediated antiviral responses, the other clone showed a lower level of resistance that involves cytoskeletal reorganization, signaling by small GTPases, and cell structural changes. These results demonstrate the capacity of tumor cells to deploy heterogeneous mechanisms of resistance to oncolytic viruses.

Hepatocellular carcinoma is characterized by high recurrence rates and poor prognosis. Cancer stem cells contribute to tumor heterogeneity, treatment resistance, and recurrence. This study aims to identify key genes associated with stemness and immune cell infiltration in HCC. We analyzed RNA sequencing data from The Cancer Genome Atlas to calculate mRNA expression-based stemness index in HCC. A weighted gene co-expression network analysis was performed to identify stemness-related gene modules. A single-sample gene set enrichment analysis was used to evaluate immune cell infiltration. Key genes were validated using RT-qPCR. The mRNAsi was significantly higher in HCC tissues compared to adjacent normal tissues and correlated with poor overall survival. WGCNA and subsequent analyses identified 10 key genes, including minichromosome maintenance complex component 2, cell division cycle 6, forkhead box M1, NIMA-related kinase 2, Holliday junction recognition protein, DNA topoisomerase II alpha, denticleless E3 ubiquitin protein ligase homolog, maternal embryonic leucine zipper kinase, protein regulator of cytokinesis 1, and kinesin family member C1, associated with stemness and low immune cell infiltration. These genes were significantly upregulated in HCC tissues. A functional enrichment analysis revealed their involvement in cell cycle regulation. This study identified 10 key genes related to stemness and immune cell infiltration in HCC. These genes, primarily involved in cell cycle regulation, may serve as potential targets for developing more effective treatments to reduce HCC recurrence and improve patient outcomes.

Cancer stem cells (CSCs) are a poorly differentiated population of malignant cells that (at least in some neoplasms) is responsible for tumor progression, resistance to therapy, and disease relapse. According to a widely accepted model, all stages of cancer progression involve the ability of neoplastic cells to evade recognition or elimination by the host immune system. In line with this notion, CSCs are not only able to cope with environmental and therapy-elicited stress better than their more differentiated counterparts but also appear to better evade tumor-targeting immune responses. We summarize epigenetic modifications of DNA and histones through which CSCs evade immune recognition or elimination, and propose that such alterations constitute promising therapeutic targets to increase the sensitivity of some malignancies to immunotherapy.

Cancer stem cells (CSCs) constitute a pivotal element within the tumor microenvironment (TME), driving the initiation and progression of cancer. However, the identification of CSCs and their underlying molecular mechanisms in laryngeal squamous cell carcinoma (LSCC) remains a formidable challenge. Here, we employed single-cell RNA sequencing of matched primary tumor tissues, paracancerous tissues, and local lymph nodes from three LSCC patients to comprehensively characterize the CSCs in LSCC. Two distinct clusters of stem cells originating from epithelial populations were delineated and verified as CSCs and normal stem cells (NSCs), respectively. CSCs were abundant in the paracancerous tissues compared to those in the tumor tissues. CSCs showed high expression of stem cell marker genes such as PROM1, ALDH1A1, and SOX4, and increased the activity of tumor-related hypoxia, Wnt/β-catenin, and Notch signaling pathways. We then explored the intricate crosstalk between CSCs and the TME cells and identified targets within the TME that related with CSCs. We also found eight marker genes of CSCs that were correlated significantly with the prognosis of LSCC patients. Furthermore, bioinformatics analyses showed that drugs such as erlotinib, OSI-027, and ibrutinib selectively targeted the CSC-specifically expressed genes. In conclusion, our results represent the first comprehensive characterization of CSC properties in LSCC at the single-cell level.

Hepatocellular Carcinoma (HCC), the most prevalent type of primary liver cancer, is known for its aggressive behavior and poor prognosis. The Cancer Stem Cell theory, which postulates the presence of a small population of self-renewing cells called Cancer Stem Cells (CSCs), provides insights into various clinical and molecular features of HCC such as tumor heterogeneity, metabolic adaptability, therapy resistance, and recurrence. These CSCs are nurtured in the tumor microenvironment (TME), where a mix of internal and external factors creates a tumor-supportive niche that is continuously evolving both spatially and temporally, thus enhancing the tumor's complexity. This review details the origins of hepatic CSCs (HCSCs) and the factors influencing their stem-like qualities. It highlights the reciprocal crosstalk between HCSCs and the TME (hypoxic, vascular, invasive, and immune niches), exploring the signaling pathways involved and how these interactions control the malignant traits of CSCs. Additionally, it discusses potential therapeutic approaches targeting the HCSC niche and their possible uses in clinical practice.

Non‑SMC condensin I complex subunit D2 (NCAPD2) is a newly identified oncogene; however, the specific biological function and molecular mechanism of NCAPD2 in liver cancer progression remain unknown. In the present study, the aberrant expression of NCAPD2 in liver cancer was investigated using public tumor databases, including TNMplot, The Cancer Genome Atlas and the International Cancer Genome Consortium based on bioinformatics analyses, and it was validated using a clinical cohort. It was revealed that NCAPD2 was significantly upregulated in liver cancer tissues compared with in control liver tissues, and NCAPD2 served as an independent prognostic factor and predicted poor prognosis in liver cancer. In addition, the expression of NCAPD2 was positively correlated with the percentage of Ki67+ cells. Finally, single‑cell sequencing data, gene‑set enrichment analyses and in vitro investigations, including cell proliferation assay, Transwell assay, wound healing assay, cell cycle experiments, cell apoptosis assay and western blotting, were carried out in human liver cancer cell lines to assess the biological mechanisms of NCAPD2 in patients with liver cancer. The results revealed that the upregulation of NCAPD2 enhanced tumor cell proliferation, invasion and cell cycle progression at the G2/M‑phase transition, and inhibited apoptosis in liver cancer cells. Furthermore, NCAPD2 overexpression was closely associated with the phosphatidylinositol 3‑kinase (PI3K)‑Akt‑mammalian target of rapamycin (mTOR)/c‑Myc signaling pathway and epithelial‑mesenchymal transition (EMT) progression in HepG2 and Huh7 cells. In addition, upregulated NCAPD2 was shown to have adverse effects on overall survival and disease‑specific survival in liver cancer. In conclusion, the overexpression of NCAPD2 was shown to lead to cell cycle progression at the G2/M‑phase transition, activation of the PI3K‑Akt‑mTOR/c‑Myc signaling pathway and EMT progression in human liver cancer cells.

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide and is associated with high morbidity and mortality. One of the main challenges in the management of HCC is late clinical presentation and thus diagnosis of the disease, which results in poor survival. The pathogenesis of HCC is complex and involves chronic liver injury and genetic alterations. Diagnosis of HCC can be made either by biopsy or imaging; however, conventional tissue-based biopsy methods and serological biomarkers such as AFP have limited clinical applications. While hepatocellular carcinoma is associated with a range of molecular alterations, including the activation of oncogenic signaling pathways, such as Wnt-TGFβ, PI3K-AKT-mTOR, RAS-MAPK, MET, IGF, and Wnt-β-catenin and TP53 and TERT promoter mutations, microfluidic applications have been limited. Early diagnosis is crucial for advancing treatments that would address the heterogeneity of HCC. In this context, microfluidic droplet-based methods are crucial, as they enable comprehensive analysis of the genome and transcriptome of individual cells. Single-cell RNA sequencing (scRNA-seq) allows the examination of individual cell transcriptomes, identifying their heterogeneity and cellular evolutionary relationships. Other microfluidic methods, such as Drop-seq, InDrop, and ATAC-seq, are also employed for single-cell analysis. Here, we examine and compare these microfluidic droplet-based methods, exploring their advantages and limitations in liver cancer research. These technologies provide new opportunities to understand liver cancer biology, diagnosis, treatment, and prognosis, contributing to scientific efforts in combating this challenging disease.

Hepatocellular carcinoma (HCC) is a highly aggressive malignant tumor with a poor prognosis. Extensive research has revealed the significant role of long noncoding RNAs (lncRNAs) in the regulation of tumor development. In this study, high-throughput sequencing analysis was used to assess the expression levels of lncRNAs in three pairs of HCC tissues and their corresponding noncancerous tissues. Through quantitative real-time polymerase chain reaction (qRT-PCR) analysis and clinicopathological analysis, it was discovered that HNF4A-AS1 was downregulated in HCC tissues. Furthermore, its expression levels were found to be positively correlated with the prognosis of HCC patients. Subsequent in vitro and in vivo functional studies demonstrated that HNF4A-AS1 inhibits the proliferation, invasion, and stemness of HCC cells. Mechanistically, it was observed that HNF4A-AS1 physically interacts with the KH3 domain of PCBP2 through a specific segment (491-672 nt). This interaction facilitates the recruitment of PCBP2 by AIP4, leading to the ubiquitination and subsequent degradation of PCBP2. Furthermore, HNF4A-AS1 was found to regulate the stability of AGR2 mRNA by modulating PCBP2, thereby influencing the malignant phenotype of HCC. Overall, our study demonstrated a positive association between the decrease in HNF4A-AS1 expression and the prognosis of patients with HCC in a clinical setting. HNF4A-AS1 can suppress the stability of ARG2 mRNA by promoting the ubiquitin-modulated degradation of PCBP2, which suppresses HCC progression. HNF4A-AS1 may serve as a potential therapeutic target for HCC.

The first-line treatment for advanced hepatocellular carcinoma has evolved significantly. This study aimed to identify the most beneficial regimen.

A systematic search was conducted from July 2012 to August 2024 across the following four databases: PubMed, Embase, Cochrane Library, and ClinicalTrials.gov. This search focused on phase III prospective randomized controlled trials that compared first-line treatment for advanced hepatocellular carcinoma.

Seventeen studies involving 10322 patients were included in this network meta-analysis. Of the studies we included, twelve studies were global multicenter clinical studies, four were initiated in China, and one was initiated in Korea. The results of our statistical analysis suggest that Hepatic artery infusion chemotherapy with oxaliplatin plus fluorouracil (HAIC-FO) demonstrated significant overall survival (OS) benefits compared with most treatments, including various immune checkpoint inhibitors (ICIs) and anti-vascular endothelial growth factor tyrosine kinase inhibitors (VEGF-TKIs). In terms of OS, HAIC had shown similar efficacy with sorafenib plus FOLFOX (HR, 0.88; 95% CI: 0.37-2.09) and transcatheter arterial chemoembolization (TACE) combined with lenvatinib (HR, 0.69; 95% CI: 0.30-1.56). Notably, immune-related treatments, such as ICIs combined with anti-VEGF therapies, also showed improved OS compared with anti-VEGF-TKIs alone. In terms of progression-free survival (PFS), HAIC-FO outperformed anti-VEGF-TKI monotherapy, ICI monotherapy, and several ICI combinations. However, it was not superior to lenvatinib plus TACE or lenvatinib plus pembrolizumab. Based on the Surface Under the Cumulative Ranking Curve (SUCRA) values, HAIC-FO was ranked the most effective in terms of OS (SUCRA = 0.961) and objective response rate (ORR) (SUCRA = 0.971). The results of the subgroup analysis suggested that HAIC-FO achieved the best OS benefit in the macrovascular invasion (MVI) and extrahepatic spread (EHS) subgroup (SUCRA = 0.99) and that tremelimumab combined with durvalumab achieved the best OS benefit in the Asian subgroup (SUCRA = 0.88).

This systematic review and network meta-analysis suggest that HAIC-based therapies may become a potential first-line treatment option for advanced HCC, especially for patients in Mainland China with MVI and EHS. Additionally, immune-related treatments may be more suitable for Asian populations.

Even though RNA treatments were first proposed as a way to change aberrant signaling in cancer, research in this field is currently ongoing. The term "RNAi" refers to the use of several RNAi technologies, including ribozymes, riboswitches, Aptamers, small interfering RNA (siRNA), antisense oligonucleotides (ASOs), and CRISPR/Cas9 technology. The siRNA therapy has already achieved a remarkable feat by revolutionizing the treatment arena of cancers. Unlike small molecules and antibodies, which need administration every three months or even every two years, RNAi may be given every quarter to attain therapeutic results. In order to overcome complex challenges, delivering siRNAs to the targeted tissues and cells effectively and safely and improving the effectiveness of siRNAs in terms of their action, stability, specificity, and potential adverse consequences are required. In this context, the three primary techniques of siRNA therapies for hepatocellular carcinoma (HCC) are accomplished for inhibiting angiogenesis, decreasing cell proliferation, and promoting apoptosis, are discussed in this review. We also deliberate targeting issues, immunogenic reactions to siRNA therapy, and the difficulties with their intrinsic chemistry and transportation.

Deregulating cellular metabolism is one of the prominent hallmarks of malignancy, with a critical role in tumor survival and growth. However, the role of reprogramming aspartate metabolism in hepatocellular carcinoma (HCC) are largely unknown.

The multi-omics data of HCC patients were downloaded from public databases. Univariate and multivariate stepwise Cox regression were used to establish an aspartate metabolism-related gene signature (AMGS) in HCC. The Kaplan-Meier and receiver operating characteristic curve analyses were performed to evaluate the predictive ability for overall survival (OS) in HCC patients. Gene set enrichment analysis and immune infiltration analysis were operated to determine the potential mechanisms underlying the AMGS. Single-cell RNA sequencing (scRNA-seq) data of liver cancer stem cells were visualized by t-SNE algorithm. In vivo and in vitro experiments were implemented to investigate the biological function of CAD in HCC. In addition, a nomogram based on the AMGS and clinicopathologic characteristics was constructed by univariate and multivariate Cox regression analyses.

Patients in the high-AMGS subgroup exerted advanced tumor status and poor prognosis. Mechanistically, the high-AMGS subgroup patients had significantly enhanced proliferation and stemness-related pathways, increased infiltration of regulatory T cells and upregulated expression levels of suppressive immune checkpoints in the tumor immune microenvironment. Notably, scRNA-seq data revealed CAD, one of the aspartate metabolism-related gene, is significantly upregulated in liver cancer stem cells. Silencing CAD inhibited proliferative capacity and stemness properties of HCC cells in vitro and in vivo. Finally, a novel nomogram based on the AMGS showed an accurate prediction in HCC patients.

The AMGS represents a promising prognostic value for HCC patients, providing a perspective for finding novel biomarkers and therapeutic targets for HCC.

Hepatocellular carcinoma (HCC) continues to play a substantial role in cancer-related morbidity and mortality, largely owing to its pronounced tumor heterogeneity and propensity for recurrence. This underscores the pressing need for in-depth examination of its highly malignant mechanisms. Annexin A5 (ANXA5), recognized as a hallmark tumor protein, has emerged as a focal point of interest because of its ambiguous function and mechanism in HCC prognosis. This study aimed to provide a comprehensive understanding of the role of ANXA5 in the malignant progression of human HCC cells by employing an integrative approach that combines conventional experimental methods with RNA sequencing.

Differences in ANXA5 expression between HCC tissues and corresponding nontumor tissues were evaluated using immunofluorescence (n = 25). Correlation analysis was subsequently performed to assess the association between ANXA5 expression and clinicopathological features (n = 65). The role of ANXA5 in human HCC cell lines with ANXA5 gene knockout and overexpression was explored in vitro using migration and invasion assays and Ki-67 indices and in vivo based on node mice xenograft model. A tube formation assay using human umbilical vein endothelial cells (HUVECs) was conducted to demonstrate the angiogenic effects of ANXA5 in HCC. Single-cell and bulk RNA sequencing was used to further investigate the underlying mechanisms involved.

This study revealed that ANXA5 is highly expressed in patients with HCC and correlates with poor prognosis. Assays for migration, invasion, and proliferation based on ANXA5 gene knockout and overexpression systems in human HCC cell lines have demonstrated that ANXA5 enhances HCC malignancy in vitro and in vivo. Tube formation assays of HUVECs indicated that ANXA5 facilitates angiogenesis and recruits endothelial cells to HCC cells. Single-cell and bulk RNA sequencing data analysis further confirmed that ANXA5 expression in HCC is associated with hepatocyte metabolism, immune response activation, and various oncogenic signaling pathways.

This study revealed a meaningful association between elevated ANXA5 expression in tumor tissues and an unfavorable prognosis in patients with HCC. In addition, ANXA5 promotes HCC malignancy by promoting invasion and angiogenesis. Thus, ANXA5 has emerged as a promising therapeutic target for HCC and has the potential to improve patient outcomes.

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.

While strides in cancer treatment continue to advance, the enduring challenges posed by cancer metastasis and recurrence persist as formidable contributors to the elevated mortality rates observed in cancer patients. Among the multifaceted factors implicated in tumor recurrence and metastasis, cancer stem cells (CSCs) emerge as noteworthy entities due to their inherent resistance to conventional therapies and heightened invasive capacities. Characterized by their notable abilities for self-renewal, differentiation, and initiation of tumorigenesis, the eradication of CSCs emerges as a paramount objective. Recent investigations increasingly emphasize the pivotal role of post-translational protein modifications (PTMs) in governing the self-renewal and replication capabilities of CSCs. This review accentuates the critical significance of several prevalent PTMs and the intricate interplay of PTM crosstalk in regulating CSC behavior. Furthermore, it posits that the manipulation of PTMs may offer a novel avenue for targeting and eliminating CSC populations, presenting a compelling perspective on cancer therapeutics with substantial potential for future applications.

Cancer stem cells (CSCs), a small subset of cells in tumors that are characterized by self-renewal and continuous proliferation, lead to tumorigenesis, metastasis, and maintain tumor heterogeneity. Cancer continues to be a significant global disease burden. In the past, surgery, radiotherapy, and chemotherapy were the main cancer treatments. The technology of cancer treatments continues to develop and advance, and the emergence of targeted therapy, and immunotherapy provides more options for patients to a certain extent. However, the limitations of efficacy and treatment resistance are still inevitable. Our review begins with a brief introduction of the historical discoveries, original hypotheses, and pathways that regulate CSCs, such as WNT/β-Catenin, hedgehog, Notch, NF-κB, JAK/STAT, TGF-β, PI3K/AKT, PPAR pathway, and their crosstalk. We focus on the role of CSCs in various therapeutic outcomes and resistance, including how the treatments affect the content of CSCs and the alteration of related molecules, CSCs-mediated therapeutic resistance, and the clinical value of targeting CSCs in patients with refractory, progressed or advanced tumors. In summary, CSCs affect therapeutic efficacy, and the treatment method of targeting CSCs is still difficult to determine. Clarifying regulatory mechanisms and targeting biomarkers of CSCs is currently the mainstream idea.

Single-cell multiomic and exosome analyses are potent tools in various fields, such as cancer research, immunology, neuroscience, microbiology, and drug development. They facilitate the in-depth exploration of biological systems, providing insights into disease mechanisms and aiding in treatment. Single-cell isolation, which is crucial for single-cell analysis, ensures reliable cell isolation and quality control for further downstream analyses. Microfluidic chips are small lightweight systems that facilitate efficient and high-throughput single-cell isolation and real-time single-cell analysis on- or off-chip. Therefore, most current single-cell isolation and analysis technologies are based on the single-cell microfluidic technology. This review offers comprehensive guidance to researchers across different fields on the selection of appropriate microfluidic chip technologies for single-cell isolation and analysis. This review describes the design principles, separation mechanisms, chip characteristics, and cellular effects of various microfluidic chips available for single-cell isolation. Moreover, this review highlights the implications of using this technology for subsequent analyses, including single-cell multiomic and exosome analyses. Finally, the current challenges and future prospects of microfluidic chip technology are outlined for multiplex single-cell isolation and multiomic and exosome analyses.

Primary liver cancer, more specifically hepatocellular carcinoma (HCC), remains a significant global health problem associated with increasing incidence and mortality. Clinical, biological, and molecular heterogeneity are well-known hallmarks of cancer and HCC is considered one of the most heterogeneous tumour types, displaying substantial inter-patient, intertumoural and intratumoural variability. This heterogeneity plays a pivotal role in hepatocarcinogenesis, metastasis, relapse and drug response or resistance. Unimodal single-cell sequencing techniques have already revolutionised our understanding of the different layers of molecular hierarchy in the tumour microenvironment of HCC. By highlighting the cellular heterogeneity and the intricate interactions among cancer, immune and stromal cells before and during treatment, these techniques have contributed to a deeper comprehension of tumour clonality, hematogenous spreading and the mechanisms of action of immune checkpoint inhibitors. However, major questions remain to be elucidated, with the identification of biomarkers predicting response or resistance to immunotherapy-based regimens representing an important unmet clinical need. Although the application of single-cell multi-omics in liver cancer research has been limited thus far, a revolution of individualised care for patients with HCC will only be possible by integrating various unimodal methods into multi-omics methodologies at the single-cell resolution. In this review, we will highlight the different established single-cell sequencing techniques and explore their biological and clinical impact on liver cancer research, while casting a glance at the future role of multi-omics in this dynamic and rapidly evolving field.

Liver cancer (LC) is a prevalent malignancy and a leading cause of cancer-related mortality worldwide. Extensive research has been conducted to enhance patient outcomes and develop effective prevention strategies, ranging from molecular mechanisms to clinical interventions. Single-cell sequencing, as a novel bioanalysis technology, has significantly contributed to the understanding of the global cognition and dynamic changes in liver cancer. However, there is a lack of bibliometric analysis in this specific research area. Therefore, the objective of this study is to provide a comprehensive overview of the knowledge structure and research hotspots in the field of single-cell sequencing in liver cancer research through the use of bibliometrics.

Publications related to the application of single-cell sequencing technology to liver cancer research as of December 31, 2023, were searched on the web of science core collection (WoSCC) database. VOSviewers, CiteSpace, and R package "bibliometrix" were used to conduct this bibliometric analysis.

A total of 331 publications from 34 countries, primarily led by China and the United States, were included in this study. The research focuses on the application of single cell sequencing technology to liver cancer, and the number of related publications has been increasing year by year. The main research institutions involved in this field are Fudan University, Sun Yat-Sen University, and the Chinese Academy of Sciences. Frontiers in Immunology and Nature Communications is the most popular journal in this field, while Cell is the most frequently co-cited journal. These publications are authored by 2799 individuals, with Fan Jia and Zhou Jian having the most published papers, and Llovet Jm being the most frequently co-cited author. The use of single cell sequencing to explore the immune microenvironment of liver cancer, as well as its implications in immunotherapy and chemotherapy, remains the central focus of this field. The emerging research hotspots are characterized by keywords such as 'Gene-Expression', 'Prognosis', 'Tumor Heterogeneity', 'Immunoregulation', and 'Tumor Immune Microenvironment'.

This is the first bibliometric study that comprehensively summarizes the research trends and developments on the application of single cell sequencing in liver cancer. The study identifies recent research frontiers and hot directions, providing a valuable reference for researchers exploring the landscape of liver cancer, understanding the composition of the immune microenvironment, and utilizing single-cell sequencing technology to guide and enhance the prognosis of liver cancer patients.

Hepatocellular carcinoma (HCC) is the most common form of liver cancer globally and remains a major cause of cancer-related deaths. HCC exhibits significant intra-tumoral and interpatient heterogeneity, impacting treatment efficacy and patient prognosis.

We acquired transcriptome data from the TCGA and ICGC databases, as well as liver cancer chip data from the GEO database, and processed the data for subsequent analysis. We also obtained single cell data from the GEO database and performed data analysis using the Seurat package. To further investigate epithelial cell subgroups and their copy number variations, we used the Seurat workflow for subgroup classification and the InferCNV software for CNV analysis, utilizing endothelial cells as a reference. Pseudo-time analysis and transcription factor analysis of epithelial cells were performed using the monocle2 and SCENIC software, respectively. To assess intercellular communication, we employed the CellChat package to identify potential ligand-receptor interactions. We also analyzed gene expression differences and conducted enrichment analysis using the limma and clusterProfiler packages. Additionally, we established tumor-related risk characteristics using Cox analysis and Lasso regression, and predicted immunotherapy response using various datasets.

The samples were classified into 23 clusters, with malignant epithelial cells being the majority. Trajectory analysis revealed the differentiation states of the malignant epithelial cells, with cluster 1 being in the terminal state. Functional analysis revealed higher aggressiveness and epithelial-mesenchymal transition (EMT) scores in cluster 1, indicating a higher propensity for metastasis. RBP4+ tumor cells were highly enriched with hypoxia process and intensive cell-to-cell communication. A prognostic model was established, and immune infiltration analysis showed increased infiltration in the high-risk group. TP53 demonstrated significant differences in mutation rate between the two risk groups. Validation analysis confirmed the up-regulation of model genes, including AKR1B10, ARL6IP4, ATP6V0B, and BSG in tumor tissues.

A prognostic model was established based on HCC malignant cell associated gene signature, displaying decent prognosis guiding effectiveness in the multiple cohorts. The study provided comprehensive insights into the heterogeneity and potential therapeutic targets of LIHC.