A unique metastasis gene signature enables prediction of tumor relapse in early-stage hepatocellular carcinoma patients

Transposable elements-mediated recruitment of KDM1A epigenetically silences HNF4A expression to promote hepatocellular carcinoma

Transposable elements (TEs) contribute to gene expression regulation by acting as cis-regulatory elements that attract transcription factors and epigenetic regulators. This research aims to explore the functional and clinical implications of transposable element-related molecular events in hepatocellular carcinoma, focusing on the mechanism through which liver-specific accessible TEs (liver-TEs) regulate adjacent gene expression. Our findings reveal that the expression of HNF4A is inversely regulated by proximate liver-TEs, which facilitates liver cancer cell proliferation. Mechanistically, liver-TEs are predominantly occupied by the histone demethylase, KDM1A. KDM1A negatively influences the methylation of histone H3 Lys4 (H3K4) of liver-TEs, resulting in the epigenetic silencing of HNF4A expression. The suppression of HNF4A mediated by KDM1A promotes liver cancer cell proliferation. In conclusion, this study uncovers a liver-TE/KDM1A/HNF4A regulatory axis that promotes liver cancer growth and highlights KDM1A as a promising therapeutic target. Our findings provide insight into the transposable element-related molecular mechanisms underlying liver cancer progression.

A novel algorithm to differentiate between primary lung tumors and distant liver metastasis in lung cancers using an exosome based multi gene biomarker panel

The lack of non-invasive methods for detection of early metastasis is a crucial reason for the poor prognosis of lung cancer (LC) liver metastasis (LM) patients. In this study, the goal was to identify circulating biomarkers based on a biomarker model for the early diagnosis and monitoring of patients with LCLM. An 8-gene panel identified in our previous study was validated in CTC, cfRNA and exosomes isolated from primary lung cancer with & without metastasis. Further multivariate analysis including PCA & ROC was performed to determine the sensitivity and specificity of the biomarker panel. Model validation cohort (n = 79) was used to verify the stability of the constructed predictive model. Further, clinic-pathological factors, survival analysis and immune infiltration correlations were also performed. In comparison to our previous tissue data, exosomes demonstrated a good discriminative value with an AUC of 0.7247, specificity (72.48%) and sensitivity (96.87%) for the 8-gene panel. Further individual gene patterns led us to a 5- gene panel that showed an AUC of 0.9488 (p =  < 0.001) and 0.9924 (p =  < 0.001) respectively for tissue and exosomes. Additionally, on validating the model in a larger cohort a risk score was obtained (RS > 0.2) for prediction of liver metastasis with an accuracy of 95%. Survival analysis and immune filtration markers suggested that four exosomal markers were independently associated with poor overall survival. We report a novel blood-based exosomal biomarker panel for early diagnosis, monitoring of therapeutic response, and prognostic evaluation of patients with LCLM.

Multi-omic profiling reveals potential biomarkers of hepatocellular carcinoma prognosis and therapy response among mitochondria-associated cell death genes in the context of 3P medicine

Background

Cancer cell growth, metastasis, and drug resistance are major challenges in treating liver hepatocellular carcinoma (LIHC). However, the lack of comprehensive and reliable models hamper the effectiveness of the predictive, preventive, and personalized medicine (PPPM/3PM) strategy in managing LIHC.

Methods

Leveraging seven distinct patterns of mitochondrial cell death (MCD), we conducted a multi-omic screening of MCD-related genes. A novel machine learning framework was developed, integrating 10 machine learning algorithms with 67 different combinations to establish a consensus mitochondrial cell death index (MCDI). This index underwent rigorous evaluation across training, validation, and in-house clinical cohorts. A comprehensive multi-omics analysis encompassing bulk, single-cell, and spatial transcriptomics was employed to achieve a deeper insight into the constructed signature. The response of risk subgroups to immunotherapy and targeted therapy was evaluated and validated. RT-qPCR, western blotting, and immunohistochemical staining were utilized for findings validation.

Results

Nine critical differentially expressed MCD-related genes were identified in LIHC. A consensus MCDI was constructed based on a 67-combination machine learning computational framework, demonstrating outstanding performance in predicting prognosis and clinical translation. MCDI correlated with immune infiltration, Tumor Immune Dysfunction and Exclusion (TIDE) score and sorafenib sensitivity. Findings were validated experimentally. Moreover, we identified PAK1IP1 as the most important gene for predicting LIHC prognosis and validated its potential as an indicator of prognosis and sorafenib response in our in-house clinical cohorts.

Conclusion

This study developed a novel predictive model for LIHC, namely MCDI. Incorporating MCDI into the PPPM framework will enhance clinical decision-making processes and optimize individualized treatment strategies for LIHC patients.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00362-8.

CDKN2 expression is a potential biomarker for T cell exhaustion in hepatocellular carcinoma

Hepatocellular Carcinoma (HCC), the predominant primary hepatic malignancy, is the prime contributor to mortality. Despite the availability of multiple surgical interventions, patient outcomes remain suboptimal. Immunotherapies have emerged as effective strategies for HCC treatment with multiple clinical advantages. However, their curative efficacy is not always satisfactory, limited by the dysfunctional T cell status. Thus, there is a pressing need to discover novel potential biomarkers indicative of T cell exhaustion (Tex) for personalized immunotherapies. One promising target is Cyclin-dependent kinase inhibitor 2 (CDKN2) gene, a key cell cycle regulator with aberrant expression in HCC. However, its specific involvement remains unclear. Herein, we assessed the potential of CDKN2 expression as a promising biomarker for HCC progression, particularly for exhausted T cells. Our transcriptome analysis of CDKN2 in HCC revealed its significant role involving in HCC development. Remarkably, single-cell transcriptomic analysis revealed a notable correlation between CDKN2 expression, particularly CDKN2A, and Tex markers, which was further validated by a human cohort study using human HCC tissue microarray, highlighting CDKN2 expression as a potential biomarker for Tex within the intricate landscape of HCC progression. These findings provide novel perspectives that hold promise for addressing the unmet therapeutic need within HCC treatment. [BMB Reports 2024; 57(6): 287-292].

RGS19 activates the MYH9/β-catenin/c-Myc positive feedback loop in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common fatal cancers worldwide, and the identification of novel treatment targets and prognostic biomarkers is urgently needed because of its unsatisfactory prognosis. Regulator of G-protein signaling 19 (RGS19) is a multifunctional protein that regulates the progression of various cancers. However, the specific function of RGS19 in HCC remains unclear. The expression of RGS19 was determined in clinical HCC samples. Functional and molecular biology experiments involving RGS19 were performed to explore the potential mechanisms of RGS19 in HCC. The results showed that the expression of RGS19 is upregulated in HCC tissues and is significantly associated with poor prognosis in HCC patients. RGS19 promotes the proliferation and metastasis of HCC cells in vitro and in vivo. Mechanistically, RGS19, via its RGS domain, stabilizes the MYH9 protein by directly inhibiting the interaction of MYH9 with STUB1, which has been identified as an E3 ligase of MYH9. Moreover, RGS19 activates β-catenin/c-Myc signaling via MYH9, and RGS19 is also a transcriptional target gene of c-Myc. A positive feedback loop formed by RGS19, MYH9, and the β-catenin/c-Myc axis was found in HCC. In conclusion, our research revealed that competition between RGS19 and STUB1 is a critical mechanism of MYH9 regulation and that the RGS19/MYH9/β-catenin/c-Myc feedback loop may represent a promising strategy for HCC therapy.

Multi-omics analysis of macrophage-associated receptor and ligand reveals a strong prognostic signature and subtypes in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a significant contributor to morbidity and mortality worldwide. The interaction between receptors and ligands is the primary mode of intercellular signaling and plays a vital role in the progression of HCC. This study aimed to identify the macrophage-related receptor ligand marker genes associated with HCC and further explored the molecular immune mechanisms attributed to altered biomarkers. Single-cell RNA sequencing data containing primary and recurrent samples were downloaded from the China National GeneBank. Cell types were first identified to explore differences between immune cells from different sample sources. CellChat analysis was used to infer and analyze intercellular communication networks quantitatively. Three molecular subtypes were constructed based on the screened twenty macrophage-associated receptor ligand genes. Bulk RNA-Seq data were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. After the screening, the minor absolute shrinkage and selection operator (LASSO) regression model was employed to identify key markers. After collecting peripheral blood and clinical information from patients, an enzyme-linked immunosorbent assay (ELISA) was used to detect the correlation between key markers and IL-10, one of the macrophage markers. After developing a new HCC risk adjustment model and conducting analysis, it was found that there were significant differences in immune status and gene mutations between the high-risk and low-risk groups of patients based on macrophage-associated receptor and ligand genes. This study identified SPP1, ANGPT2, and NCL as key biological targets for HCC. The drug-gene interaction network analysis identified wortmannin, ribavirin, and tarnafloxin as potential therapeutic drugs for the three key markers. In a clinical cohort study, patients with immune checkpoint inhibitor (ICI) resistance had significantly higher expression levels of OPN, ANGPT2, NCL, and IL-10 than patients with ICI-responsiveness. These three key markers were positively correlated with the expression level of IL-10. The signature based on macrophage-associated receptor and ligand genes can accurately predict the prognosis of patients with HCC and the sensitivity to immunotherapy. These results may help guide the development of targeted prevention and personalized treatment of HCC.

SOAT1 regulates cholesterol metabolism to induce EMT in hepatocellular carcinoma

Cholesterol metabolism reprogramming is one of the significant characteristics of hepatocellular carcinoma (HCC). Cholesterol increases the risk of epithelial-mesenchymal transition (EMT) in cancer. Sterol O-acyltransferases 1 (SOAT1) maintains the cholesterol homeostasis. However, the exact mechanistic contribution of SOAT1 to EMT in HCC remains unclear. Here we demonstrated that SOAT1 positively related to poor prognosis of HCC, EMT markers and promoted cell migration and invasion in vitro, which was mediated by the increased cholesterol in plasmalemma and cholesterol esters accumulation. Furthermore, we reported that SOAT1 disrupted cholesterol metabolism homeostasis to accelerate tumorigenesis and development in HCC xenograft and NAFLD-HCC. Also, we detected that nootkatone, a sesquiterpene ketone, inhibited EMT by targeting SOAT1 in vitro and in vivo. Collectively, our finding indicated that SOAT1 promotes EMT and contributes to hepatocarcinogenesis by increasing cholesterol esterification, which is suppressed efficiently by nootkatone. This study demonstrated that SOAT1 is a potential biomarker and therapeutic target in NAFLD-HCC and SOAT1-targeting inhibitors are expected to be the potential new therapeutic treatment for HCC.

Machine learning and multi-omics data reveal driver gene-based molecular subtypes in hepatocellular carcinoma for precision treatment

The heterogeneity of Hepatocellular Carcinoma (HCC) poses a barrier to effective treatment. Stratifying highly heterogeneous HCC into molecular subtypes with similar features is crucial for personalized anti-tumor therapies. Although driver genes play pivotal roles in cancer progression, their potential in HCC subtyping has been largely overlooked. This study aims to utilize driver genes to construct HCC subtype models and unravel their molecular mechanisms. Utilizing a novel computational framework, we expanded the initially identified 96 driver genes to 1192 based on mutational aspects and an additional 233 considering driver dysregulation. These genes were subsequently employed as stratification markers for further analyses. A novel multi-omics subtype classification algorithm was developed, leveraging mutation and expression data of the identified stratification genes. This algorithm successfully categorized HCC into two distinct subtypes, CLASS A and CLASS B, demonstrating significant differences in survival outcomes. Integrating multi-omics and single-cell data unveiled substantial distinctions between these subtypes regarding transcriptomics, mutations, copy number variations, and epigenomics. Moreover, our prognostic model exhibited excellent predictive performance in training and external validation cohorts. Finally, a 10-gene classification model for these subtypes identified TTK as a promising therapeutic target with robust classification capabilities. This comprehensive study provides a novel perspective on HCC stratification, offering crucial insights for a deeper understanding of its pathogenesis and the development of promising treatment strategies.

Cuproptosis-associated genes (CAGs) contribute to the prognosis prediction and potential therapeutic targets in hepatocellular carcinoma

BACKGROUND

Cuproptosis is a novel form of cell death that exhibits close association with mitochondrial respiration and occurs through distinct mechanisms compared to previously characterized forms of cell death. However, the precise impact of cuproptosis-associated genes (CAGs) on prognosis, immune profiles, and treatment efficacy in hepatocellular carcinomas (HCC) remains poorly understood.

METHODS

A comprehensive analysis of CAGs in hepatocellular carcinoma (HCC) prognosis was conducted using genomic data from HCC patients. Consensus clustering analysis was performed to determine molecular subtypes related to cuproptosis in HCC. The single-sample gene set enrichment analysis (ssGSEA) algorithm was applied to quantify the infiltration levels of immune cells, while the "ESTIMATE" package was employed to calculate tumor purity, stromal scores, and immune scores in the tumor microenvironment (TME). Principal component analysis (PCA) algorithm was utilized to construct a risk score related to CAGs. Finally, CCK8, wound healing, Transwell migration/invasion, EDU and xenograft model were employed to explore the potential oncogenic role of MTF1.

RESULTS

Three distinct patterns of cuproptosis modification were identified, each associated with unique functional enrichments, clinical characteristics, immune cell infiltration, immune checkpoints, tumor microenvironment (TME), and prognosis. A CAGs-related risk score (Cuscore) was developed to predict prognosis in TCGA and validated in GSE76427 and ICGC datasets. Notably, patients with a low Cuscore had better prognoses and were more likely to benefit from immunotherapy.Additionally, the high Cuscore group in HCC also revealed three potential therapeutic targets (TUBA1B, CDC25B, and CSNK2A1) as well as several therapeutic compounds. Moreover, the experiment measured the expression levels of six prognosis-related CAGs, wherein knockdown of MTF1 exhibited suppression of proliferation, invasion, and migration formation in HCC cell lines.

CONCLUSION

The findings have enhanced our comprehension of the cuproptosis characteristics in HCC, and stratification based on CuScore may potentially enhance the prediction of patients' prognosis and facilitate the development of effective and innovative treatment strategies.

Quantitative proteomics assay reveals G protein-coupled receptor kinase 4-induced HepG2 cell growth inhibition

Background and aim

To investigate the biological effects and putative biological mechanism of G protein-coupled receptor kinase 4 (GRK4) on HepG2 cells.

Materials and methods

Cell proliferation, cycle, and apoptosis were evaluated by Cell Counting Kit-8 and flow cytometry (FCM) in HepG2 cells infected with either the GRK4-overexpressing lentivirus vector (OE) or the negative control lentivirus vector (NC). The protein profiles and differentially expressed proteins (DEPs) of the OE and NC cells were analyzed and compared using the quantitative proteomics technique, and their function, expression, and probable mechanism were investigated using bioinformatic assays and parallel reaction monitoring (PRM).

Results

HepG2 cells that received the OE grew more slowly than those that received the NC. FCM revealed that, when compared to the NC cells, the OE cells had undergone S-phase cycle arrest, and neither the OE nor NC cells underwent apoptosis. Among the 7006 proteins that were identified by quantitative proteomics, 403 DEPs were examined based on the filtering parameters, with the expressions of 135 being downregulated and 268 being upregulated. In addition to being involved in the peroxisome proliferator-activated receptor (PPAR) signaling pathway, the DEPs were implicated in the biological processes of cell proliferation, cycle, and metabolism. PRM verified the expressions of DEPs that were connected to the PPAR pathway.

Conclusions

This study shows that GRK4 prevents HepG2 cells from proliferating and causes cell cycle arrest in the S-phase, while the PPAR pathway is involved in the regulation of HepG2 cells via GRK4.

TIF1γ and SMAD4 regulation in colorectal cancer: impact on cell proliferation and liver metastasis

We investigated the effects of transcriptional intermediary factor 1γ (TIF1γ) and SMAD4 on the proliferation and liver metastasis of colorectal cancer (CRC) cells through knockdown of TIF1γ and/or SMAD4 and knockdown of TIF1γ and/or restoration of SMAD4 expression. Furthermore, we examined TIF1γ and SMAD4 expression in human primary CRC and corresponding liver metastatic CRC specimens. TIF1γ promoted but SMAD4 inhibited the proliferation of CRC cells by competitively binding to activated SMAD2/SMAD3 complexes and then reversely regulating c-Myc, p21, p27, and cyclinA2 levels. Surprisingly, both TIF1γ and SMAD4 reduced the liver metastasis of all studied CRC cell lines via inhibition of MEK/ERK pathway-mediated COX-2, Nm23, uPA, and MMP9 expression. In patients with advanced CRC, reduced TIF1γ or SMAD4 expression was correlated with increased invasion and liver metastasis and was a significant, independent risk factor for recurrence and survival after radical resection. Patients with advanced CRC with reduced TIF1γ or SAMD4 expression had higher recurrence rates and shorter overall survival. TIF1γ and SMAD4 competitively exert contrasting effects on cell proliferation but act complementarily to suppress the liver metastasis of CRC via MEK/ERK pathway inhibition. Thus, reduced TIF1γ or SMAD4 expression in advanced CRC predicts earlier liver metastasis and poor prognosis.

A prognostic and immune related risk model based on zinc homeostasis in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. The dysfunction of zinc homeostasis participates in the early and advancing malignancy of HCC. However, the prognostic ability of zinc homeostasis in HCC has not been clarified yet. Here, we showed a zinc-homeostasis related risk model in HCC. Five signature genes including ADAMTS5, PLOD2, PTDSS2, KLRB1, and UCK2 were screened out via survival analyses and regression algorithms to construct the nomogram with clinical characteristics. Experimental researches indicated that UCK2 participated in the progression of HCC. Patients with higher risk scores always had worse outcomes and were more associated with immune suppression according to the analyses of immune related-pathway activation, cell infiltration, and gene expression. Moreover, these patients were likely to exhibit more sensitivity to sorafenib and other antitumor drugs. This study highlights the significant prognostic role of zinc homeostasis and suggests potential treatment strategies in HCC.

Tumor phylogeography reveals block-shaped spatial heterogeneity and the mode of evolution in Hepatocellular Carcinoma

Solid tumors are complex ecosystems with heterogeneous 3D structures, but the spatial intra-tumor heterogeneity (sITH) at the macroscopic (i.e., whole tumor) level is under-explored. Using a phylogeographic approach, we sequence genomes and transcriptomes from 235 spatially informed sectors across 13 hepatocellular carcinomas (HCC), generating one of the largest datasets for studying sITH. We find that tumor heterogeneity in HCC segregates into spatially variegated blocks with large genotypic and phenotypic differences. By dissecting the transcriptomic heterogeneity, we discover that 30% of patients had a "spatially competing distribution" (SCD), where different spatial blocks have distinct transcriptomic subtypes co-existing within a tumor, capturing the critical transition period in disease progression. Interestingly, the tumor regions with more advanced transcriptomic subtypes (e.g., higher cell cycle) often take clonal dominance with a wider geographic range, rejecting neutral evolution for SCD patients. Extending the statistical tests for detecting natural selection to many non-SCD patients reveal varying levels of selective signal across different tumors, implying that many evolutionary forces including natural selection and geographic isolation can influence the overall pattern of sITH. Taken together, tumor phylogeography unravels a dynamic landscape of sITH, pinpointing important evolutionary and clinical consequences of spatial heterogeneity in cancer.

Prognostic Value of S100 Family mRNA Expression in Hepatocellular Carcinoma

BACKGROUND/AIMS

 The S100 family contains more than 20 Ca2+-binding proteins that participate in numerous cellular biological processes. However, the prognostic value of individual S100s in hepatocellular carcinoma (HCC) remains unclear. Therefore, we comprehensively assessed the prognostic value of S100s in HCC.

MATERIALS AND METHODS

 The mRNA level of S100s in distinct types of cancer was analyzed through Oncomine. The clinical prognostic significance of each S100 was evaluated using Kaplan-Meier plotter and OncoLnc. The expression and mutation of S100s were determined through cBioPortal. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were used to predict the functions and pathways of S100s.

RESULTS

 The analyses revealed that, relative to normal tissues, liver cancer tissues showed aberrant mRNA expression of most S100s. In the survival analysis with Kaplan-Meier plotter, elevated expression levels of S100PBP, S100A2, S100A7, S100A10, and S100A13 were related to shorter overall survival (OS), whereas increased S100A5 expression was associated with longer OS. Moreover, results obtained using OncoLnc showed that increased expression levels of S100P, S100PBP, S100A13, S100A11, S100A10, and S100A2 were related to shorter OS. Thus, S100PBP, S100A13, S100A10, and S100A2 exhibited the same prognostic trend in the 2 databases. However, all S100 member gene mutational changes had no considerable prognostic value in OS and disease-free survival of HCC patients.

CONCLUSION

 Although the findings need to be further confirmed by experiments, they provide new evidence for the prognostic significance of the S100s in HCC.

TGFβR1 inhibition drives hepatocellular carcinoma proliferation through induction of toll-like-receptor signalling

Transforming growth factor (TGF)-β and toll-like receptors (TLRs) have been shown to independently modulate the proliferation of hepatocellular carcinoma (HCC). Since a direct cross-talk between these two signalling pathways in HCC has not been clearly described before, we aimed here to explore the possibility of such interaction. A human HCC tissue array (n = 20 vs. four control samples), human HCC samples (n = 10) and steatohepatitis-driven murine HCC samples (control, NASH and HCC; n = 6/group) were immunostained for TGFβR1, pSMAD2, TRAF6, IRAK1 and PCNA. The results were confirmed by immunoblotting. Effects of constant activation of the SMAD pathway by constitutive expression of ALK5 or knockdown of mediators of TLR signalling, IRAK1 and MyD88, on HCC proliferation, were investigated in the HCC cell line (HUH-7) after treatment with TGFβ1 cytokine or TGFβR1 kinase inhibitor (LY2157299) using PCNA and MTS assay. TGFβR1 expression is decreased in human and murine HCC and associated with downregulated pSMAD2, but increased IRAK1, TRAF6 and PCNA staining. TGFβR1 kinase inhibition abolished the cytostatic effects of TGFβ1 and led to the induction of IRAK1, pIRAK1 and elevated mRNA levels of TLR-9. Overexpression of ALK5 and knockdown of MyD88 or IRAK1 augmented the cytostatic effects of TGFβ1 on HUH-7. In another epithelial HCC cell line, that is, HepG2, TGFβR1 kinase inhibitor similarly elevated cellular proliferation. There is a balance between the canonical SMAD-driven tumour-suppressing arm and the non-canonical tumour-promoting arm of TGFβ signalling. Disruption of this balance, by inhibition of the canonical pathway, induces HCC proliferation through TLR signalling.

Role of CCR1/5/7 in hepatocellular carcinoma: a study on prognostic evaluation, molecular subtyping, and association with immune infiltration

This study aims to assess the prognostic value of the C-C motif chemokine receptor (CCR) gene family in hepatocellular carcinoma (HCC) and its relationship with immune infiltration and molecular subtypes of HCC. The evaluation of the GSE14520 dataset and TCGA database confirmed the prognostic significance of CCR. Building upon the correlation between CCR1, CCR5, and CCR7 and favorable prognosis, we further validated the prognostic importance of CCR1, CCR5, and CCR7 in ICGC database and an independent cohort from Guangxi autonomous region. Then, we constructed a risk prognosis model. Additionally, we observed significant positive correlations between CCR1, CCR5, and CCR7 and the infiltration of B cells, T cells, and macrophages in HCC. Subsequently, we conducted CCK assays, Transwell assays, and colony formation assays to evaluate the molecular biological functions of CCR1, CCR5, and CCR7. These experiments further confirmed that upregulation of CCR1, CCR5, and CCR7 can individually inhibit the proliferation, migration, and stemness of HCC cells. By analyzing the relationship between expression levels and tumor mutation frequency, we discovered that patients with high CCR1 expression were more likely to be classified as non-proliferative HCC. Similar conclusions were observed for CCR5 and CCR7. The association of CCR1, CCR5, and CCR7 with the molecular subtypes of HCC suggests that they may serve as intermediary molecules linking immune status and molecular subtypes in HCC. In summary, CCR1, CCR5, and CCR7 have the potential to serve as prognostic biomarkers for HCC and regulate HCC progression by influencing immune cell infiltration.

SEPTIN10-mediated crosstalk between cytoskeletal networks controls mechanotransduction and oncogenic YAP/TAZ signaling

The transcriptional co-activators of the Hippo pathway, YAP and TAZ, are regulated by mechanotransduction, which depends on dynamic actin cytoskeleton remodeling. Here, we identified SEPTIN10 as a novel cytoskeletal protein, which is transcriptionally regulated by YAP/TAZ and whose overexpression correlates with poor survival and vascular invasion in hepatocellular carcinoma (HCC) patients. Functional characterization demonstrated that SEPTIN10 promotes YAP/TAZ-dependent cell viability, migration and invasion of liver cancer cells. Mechanistically, SEPTIN10 interacts with actin and microtubule filaments supporting actin stress fiber formation and intracellular tension through binding to CAPZA2 while concurrently inhibiting microtubule polymerization through the blockage of MAP4 function. This functional antagonism is important for cytoskeleton-dependent feedback activation of YAP/TAZ, as microtubule depolymerization induces actin stress fiber formation and subsequently YAP/TAZ activity. Importantly, the crosstalk between microfilaments and microtubules is mediated by SEPTIN10 as its loss abrogates actin stress fiber formation after microtubule disruption. Together, the YAP/TAZ target gene SEPTIN10 controls the dynamic interplay between actin and microtubule filaments, which feeds back on Hippo pathway activity in HCC cells and thus acts as molecular switch with impact on oncogenic signaling and cancer cell biology.

The transcription factor ChREBP Orchestrates liver carcinogenesis by coordinating the PI3K/AKT signaling and cancer metabolism

Cancer cells integrate multiple biosynthetic demands to drive unrestricted proliferation. How these cellular processes crosstalk to fuel cancer cell growth is still not fully understood. Here, we uncover the mechanisms by which the transcription factor Carbohydrate responsive element binding protein (ChREBP) functions as an oncogene during hepatocellular carcinoma (HCC) development. Mechanistically, ChREBP triggers the expression of the PI3K regulatory subunit p85α, to sustain the activity of the pro-oncogenic PI3K/AKT signaling pathway in HCC. In parallel, increased ChREBP activity reroutes glucose and glutamine metabolic fluxes into fatty acid and nucleic acid synthesis to support PI3K/AKT-mediated HCC growth. Thus, HCC cells have a ChREBP-driven circuitry that ensures balanced coordination between PI3K/AKT signaling and appropriate cell anabolism to support HCC development. Finally, pharmacological inhibition of ChREBP by SBI-993 significantly suppresses in vivo HCC tumor growth. Overall, we show that targeting ChREBP with specific inhibitors provides an attractive therapeutic window for HCC treatment.

Lineage and ecology define liver tumor evolution in response to treatment

A tumor ecosystem constantly evolves over time in the face of immune predation or therapeutic intervention, resulting in treatment failure and tumor progression. Here, we present a single-cell transcriptome-based strategy to determine the evolution of longitudinal tumor biopsies from liver cancer patients by measuring cellular lineage and ecology. We construct a lineage and ecological score as joint dynamics of tumor cells and their microenvironments. Tumors may be classified into four main states in the lineage-ecological space, which are associated with clinical outcomes. Analysis of longitudinal samples reveals the evolutionary trajectory of tumors in response to treatment. We validate the lineage-ecology-based scoring system in predicting clinical outcomes using bulk transcriptomic data of additional cohorts of 716 liver cancer patients. Our study provides a framework for monitoring tumor evolution in response to therapeutic intervention.

GCF2 mediates nicotine-induced cancer stemness and progression in hepatocellular carcinoma

Cigarette smoking is one of the most impactful behavior-related risk factors for multiple cancers including hepatocellular carcinoma (HCC). Nicotine, as the principal component of tobacco, is not only responsible for smoking addiction but also a carcinogen; nevertheless, the underlying mechanisms remain unclear. Here we report that nicotine enhances HCC cancer stemness and malignant progression by upregulating the expression of GC-rich binding factor 2 (GCF2), a gene that was revealed to be upregulated in HCC and whose upregulation predicts poor prognosis, and subsequently activating the Wnt/ꞵ-catenin/SOX2 signaling pathway. We found that nicotine significantly increased GCF2 expression and that silencing of GCF2 reduced nicotine-induced cancer stemness and progression. Mechanistically, nicotine could stabilize the protein level of GCF2, and then GCF2 could robustly activate its downstream Wnt/β-catenin signaling pathway. Taken together, our results thus suggest that GCF2 is a potential target for a therapeutic strategy against nicotine-promoted HCC.

Construction of immune-related molecular diagnostic and predictive models of hepatocellular carcinoma based on machine learning

Background

To exploit hepatocellular carcinoma (HCC) diagnostic substances, we identify potential predictive markers based on machine learning and to explore the significance of immune cell infiltration in this pathology.

Method

Three HCC gene expression datasets were used for weighted gene co-expression network analysis (WGCNA) and differential expression analysis. Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest were applied to identify candidate biomarkers. The diagnostic value of HCC diagnostic gene biomarkers was further assessed by the area under the ROC curve observed in the validation dataset. CIBERSORT was used to analyze 22 immune cell fractions from HCC patients and to analyze their correlation with diagnostic markers. In addition, the prognostic value of the markers and the sensitivity of the drugs were analyzed.

Result

WGCNA and differential expression analysis were used to screen 396 distinct gene signatures in HCC tissues. They were mostly engaged in cytoplasmic fusion and the cell division cycle, according to gene enrichment analyses. Five genes were shown to have a high diagnostic value for use as diagnostic biomarkers for HCC, including EFHD1 (AUC = 0.77), KIF4A (AUC = 0.97), UBE2C (AUC = 0.96), SMYD3 (AUC = 0.91), and MCM7 (AUC = 0.93). T cells, NK cells, macrophages, and dendritic cells were found to be related to diagnostic markers in HCC tissues by immune cell infiltration analysis, indicating that these cells are intimately linked to the onset and spread of HCC. Concurrently, these five genes and their constructed models have considerable prognostic value.

Conclusion

These five genes (EFHD1, KIF4A, UBE2C, SMYD3, and MCM7) may serve as new candidate molecular markers for HCC, providing new insights for future diagnosis, prognosis, and molecular therapy of HCC.

MyD88 signaling pathways: role in breast cancer

MyD88 plays a central role in breast cancer, exerting a multitude of effects that carry substantial implications. Elevated MyD88 expression is closely associated with aggressive tumor characteristics, suggesting its potential as a valuable prognostic marker and therapeutic target. MyD88 exerts influence over several critical aspects of breast cancer, including metastasis, recurrence, drug resistance, and the regulation of cancer stem cell properties. Furthermore, MyD88 modulates the release of inflammatory and chemotactic factors, thereby shaping the tumor's immune microenvironment. Its role in immune response modulation underscores its potential in influencing the dynamic interplay between tumors and the immune system. MyD88 primarily exerts intricate effects on tumor progression through pathways such as Phosphoinositide 3-kinases/Protein kinase B (PI3K/Akt), Toll-like Receptor/Nuclear Factor Kappa B (TLR/NF-κB), and others. Nevertheless, in-depth research is essential to unveil the precise mechanisms underlying the diverse roles of MyD88 in breast cancer. The translation of these findings into clinical applications holds great promise for advancing precision medicine approaches for breast cancer patients, ultimately enhancing prognosis and enabling the development of more effective therapeutic strategies.

The Role of GNMT and MMP12 Expression in Determining TACE Efficacy: Validation at Transcription and Protein Levels

Purpose

Transarterial chemoembolization (TACE) represents a significant therapeutic modality for hepatocellular carcinoma (HCC). We aimed to develop a gene signature to accurately predict patient TACE response and explore the underlying mechanisms.

Methods

Three independent datasets were utilized, including GSE104580, GSE14520 and external validation from the Cancer Hospital Chinese Academy of Medical Sciences. GSE104580 was randomly partitioned into a training set and a validation set, whereas GSE14520 was categorized into a resection group and a TACE group. Logistic regression was used to develop a TACE effectiveness model. Immunohistochemistry is utilized to confirm the protein expression trends of the signature genes. Immune infiltration and functional enrichment analyses were conducted to investigate the potential underlying mechanisms.

Results

A 2-gene signature consisting of glycine N-methyltransferase (GNMT) and matrix metalloproteinase-12 (MMP12) was constructed, and based on this, all the patients were assigned TACE effectiveness scores and categorized into high effectiveness (HE) and low effectiveness (LE) groups. The HE group exhibited a better prognosis than the LE group in the various cohorts (p < 0.05). In the external validation set, immunohistochemistry confirmed the expression of the signature genes exhibiting an upregulated trend of GNMT in the HE group and MMP12 in the LE group, the LE group also exhibited a poorer prognosis [for overall survival (OS), HE group: 881 days vs LE group: 273 days (p < 0.05), and for progression-free survival (PFS), HE group: 458 days vs LE group: 136 days (p < 0.05)]. Multivariate analysis in all the datasets identified LE status as an independent risk factor for OS, disease-free survival (DFS) and PFS. The infiltration level of M0 macrophages and activated mast cells in the LE group was significantly higher than in the HE group. The hypoxia signaling pathway and glycolysis pathway were significantly enriched in the LE group.

Conclusion

The loss of GNMT and the overexpression of MMP12 may be critical factors influencing TACE efficacy.

Establishment and Validation of Novel Prognostic Subtypes in Hepatocellular Carcinoma Based on Bile Acid Metabolism Gene Signatures Using Bulk and Single-Cell RNA-Seq Data

Hepatocellular carcinoma (HCC) is a highly detrimental cancer type and has limited therapeutic options, posing significant threats to human health. The development of HCC has been associated with a disorder in bile acid (BA) metabolism. In this study, we employed an integrative approach, combining various datasets and omics analyses, to comprehensively characterize the tumor microenvironment in HCC based on genes related to BA metabolism. Our analysis resulted in the classification of HCC samples into four subtypes (C1, C2a, C2b, and C3). Notably, subtype C2a, characterized by the highest bile acid metabolism score (BAMS), exhibited the highest survival probability. This subtype also demonstrated increased immune cell infiltration, lower cell cycle scores, reduced AFP levels, and a lower risk of metastasis compared to subtypes C1 and C3. Subtype C1 displayed poorer survival probability and elevated cell cycle scores. Importantly, the identified subtypes based on BAMS showed potential relevance to the gene expression of drug targets in currently approved drugs and those under clinical research. Genes encoding VEGFR (FLT4 and KDR) and MET were elevated in C2, while genes such as TGFBR1, TGFB1, ADORA3, SRC, BRAF, RET, FLT3, KIT, PDGFRA, and PDGFRB were elevated in C1. Additionally, FGFR2 and FGFR3, along with immune target genes including PDCD1 and CTLA4, were higher in C3. This suggests that subtypes C1, C2, and C3 might represent distinct potential candidates for TGFB1 inhibitors, VEGFR inhibitors, and immune checkpoint blockade treatments, respectively. Significantly, both bulk and single-cell transcriptome analyses unveiled a negative correlation between BA metabolism and cell cycle-related pathways. In vitro experiments further confirmed that the treatment of HCC cell lines with BA receptor agonist ursodeoxycholic acid led to the downregulation of the expression of cell cycle-related genes. Our findings suggest a plausible involvement of BA metabolism in liver carcinogenesis, potentially mediated through the regulation of tumor cell cycles and the immune microenvironment. This preliminary understanding lays the groundwork for future investigations to validate and elucidate the specific mechanisms underlying this potential association. Furthermore, this study provides a novel foundation for future precise molecular typing and the design of systemic clinical trials for HCC therapy.

Smad4 sequestered in SFPQ condensates prevents TGF-β tumor-suppressive signaling

Loss of TGF-β growth-inhibitory responses is a hallmark of human cancer. However, the molecular mechanisms underlying the TGF-β resistance of cancer cells remain to be fully elucidated. Splicing factor proline- and glutamine-rich (SFPQ) is a prion-like RNA-binding protein that is frequently upregulated in human cancers. In this study, we identified SFPQ as a potent suppressor of TGF-β signaling. The ability of SFPQ to suppress TGF-β responses depends on its prion-like domain (PrLD) that drives liquid-liquid phase separation (LLPS). Mechanistically, SFPQ physically restrained Smad4 in its condensates, which excluded Smad4 from the Smad complex and chromatin occupancy and thus functionally dampened Smad-dependent transcriptional responses. Accordingly, SFPQ deficiency or loss of phase separation activities rendered human cells hypersensitive to TGF-β responses. Together, our data identify an important function of SFPQ through LLPS that suppresses Smad transcriptional activation and TGF-β tumor-suppressive activity.

Identification of Proteome-Based Immune Subtypes of Early Hepatocellular Carcinoma and Analysis of Potential Metabolic Drivers

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, ranking fourth in frequency. The relationship between metabolic reprogramming and immune infiltration has been identified as having a crucial impact on HCC progression. However, a deeper understanding of the interplay between the immune system and metabolism in the HCC microenvironment is required. In this study, we used a proteomic dataset to identify three immune subtypes (IM1-IM3) in HCC, each of which has distinctive clinical, immune, and metabolic characteristics. Among these subtypes, IM3 was found to have the poorest prognosis, with the highest levels of immune infiltration and T-cell exhaustion. Furthermore, IM3 showed elevated glycolysis and reduced bile acid metabolism, which was strongly correlated with CD8 T cell exhaustion and regulatory T cell accumulation. Our study presents the proteomic immune stratification of HCC, revealing the possible link between immune cells and reprogramming of HCC glycolysis and bile acid metabolism, which may be a viable therapeutic strategy to improve HCC immunotherapy.

Arachidonic acid metabolism CYP450 pathway is deregulated in hepatocellular carcinoma and associated with microvascular invasion

Arachidonic acid metabolism plays a crucial role in the development and progression of inflammatory and metabolic liver diseases. However, its role in hepatocellular carcinoma (HCC) remains unclear. In this study, we investigated the expression of key genes involved in the arachidonic acid metabolism pathway in HCC using a combination of bioinformatics, proteomics and immunohistochemistry analyses. Through a comprehensive analysis of publicly available datasets, clinical HCC tissues, and tissue microarrays, we compared the expression of hepatic arachidonic acid metabolic genes. We observed significant downregulation of cytochrome P450 (CYP450) pathway genes at both the messenger RNA and protein levels in HCC tissues compared to normal liver tissues. Furthermore, we observed a strong correlation between the deregulation of the arachidonic acid metabolism CYP450 pathway and the pathological features and prognosis of HCC. Specifically, the expression of CYP2C8/9/18/19 was significantly correlated with pathological grade (r = -.484, p < .0001), vascular invasion (r = -.402, p < .0001), aspartate transaminase (r = -.246, p = .025), gamma-glutamyl transpeptidase (r = -.252, p = .022), alkaline phosphatase (r = -.342, p = .002), alpha-fetoprotein (r = -.311, p = .004) and carbohydrate antigen 19-9 (r = -.227, p = .047). Moreover, we discovered a significant association between CYP450 pathway activity and vascular invasion in HCC. Collectively, these data indicate that arachidonic acid CYP450 metabolic pathway deregulation is implicated in HCC progression and may be a potential predictive factor for early recurrence in patients with HCC.

Development of a Combined Oxidative Stress and Endoplasmic Reticulum Stress-Related Prognostic Signature for Hepatocellular Carcinoma

BACKGROUND

Oxidative stress and endoplasmic reticulum stress are important components of the cellular stress process, which plays a critical role in tumor initiation and progression.

METHODS

First, the correlation between oxidative stress and endoplasmic reticulum stress was detected in 68 human hepatocellular carcinoma (HCC) tissue microarray samples by immunohistochemistry. Differentially expressed oxidative stress- and endoplasmic reticulum stressrelated genes (OESGs) then were screened in HCC. Next, an OESGs prognostic signature was constructed for HCC in the training cohort (TCGA-LIHC from The Cancer Genome Atlas), by least absolute shrinkage and selection operator Cox and stepwise Cox regression analyses, and was verified in the external cohort (GSE14520 from the Gene Expression Omnibus). The MCP counter was employed to evaluate immune cell infiltration. The C-index was used to evaluate the predictive power of prognostic signature. Finally, a prognostic nomogram model was constructed to predict the survival probability of patients with HCC based on the results of Cox regression analysis.

RESULTS

We demonstrated a positive correlation between oxidative stress and endoplasmic reticulum stress in human HCC samples. We then identified five OESGs as a prognostic signature consisting of IL18RAP, ECT2, PPARGC1A, STC2, and NQO1 for HCC. Related risk scores correlated with tumor stage, grade, and response to transcatheter arterial chemoembolization therapy, and the higher risk score group had less T cells, CD8+ T cells, cytotoxic lymphocytes and natural killer cell infiltration. The C-index of our OESGs prognostic signature was superior to four previously published signatures. Furthermore, we developed a nomogram based on the OESGs prognostic signature and clinical parameters for patients with HCC that is an effective quantitative analysis tool to predict patient survival.

CONCLUSION

The OESGs signature showed excellent performance in predicting survival and therapeutic responses for patients with HCC.

Components of the JNK-MAPK pathway play distinct roles in hepatocellular carcinoma

PURPOSE

Mitogen-activated protein kinases (MAPK), specifically the c-Jun N-terminal kinase (JNK)-MAPK subfamily, play a crucial role in the development of various cancers, including hepatocellular carcinoma (HCC). However, the specific roles of JNK1/2 and their upstream regulators, MKK4/7, in HCC carcinogenesis remain unclear.

METHODS

In this study, we performed differential expression analysis of JNK-MAPK components at both the transcriptome and protein levels using TCGA and HPA databases. We utilized Kaplan-Meier survival plots and receiver operating characteristic (ROC) curve analysis to evaluate the prognostic performance of a risk scoring model based on these components in the TCGA-HCC cohort. Additionally, we conducted immunoblotting, apoptosis analysis with FACS and soft agar assays to investigate the response of JNK-MAPK pathway components to various death stimuli (TRAIL, TNF-α, anisomycin, and etoposide) in HCC cell lines.

RESULTS

JNK1/2 and MKK7 levels were significantly upregulated in HCC samples compared to paracarcinoma tissues, whereas MKK4 was downregulated. ROC analyses suggested that JNK2 and MKK7 may serve as suitable diagnostic genes for HCC, and high JNK2 expression correlated with significantly poorer overall survival. Knockdown of JNK1 enhanced TRAIL-induced apoptosis in hepatoma cells, while JNK2 knockdown reduced TNF-α/cycloheximide (CHX)-and anisomycin-induced apoptosis. Neither JNK1 nor JNK2 knockdown affected etoposide-induced apoptosis. Furthermore, MKK7 knockdown augmented TNF-α/CHX- and TRAIL-induced apoptosis and inhibited colony formation in hepatoma cells.

CONCLUSION

Targeting MKK7, rather than JNK1/2 or MKK4, may be a promising therapeutic strategy to inhibit the JNK-MAPK pathway in HCC therapy.

Identification and validation of candidate clinical signatures of apolipoprotein L isoforms in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a lethal malignancy worldwide with an increasing number of new cases each year. Apolipoprotein (APOL) isoforms have been explored for their associations with HCC.The GSE14520 cohort was used for training data; The Cancer Genome Atlas (TCGA) database was used for validated data. Diagnostic, prognostic significance and mechanisms were explored using these cohorts. Risk score models and nomograms were constructed using prognosis-related isoforms and clinical factors for survival prediction. Oncomine and HCCDB databases were further used for validation of diagnostic, prognostic significance. APOL1, 3, and 6 were differentially expressed in two cohorts (all P ≤ 0.05). APOL1 and APOL6 had diagnostic capacity whereas APOL3 and APOL6 had prognostic capacity in two cohorts (areas under curves [AUCs] > 0.7, P ≤ 0.05). Mechanism studies demonstrated that APOL3 and APOL6 might be involved in humoral chemokine signaling pathways (all P ≤ 0.05). Risk score models and nomograms were constructed and validated for survival prediction of HCC. Moreover, diagnostic values of APOL1 and weak APOL6 were validated in Oncomine database (AUC > 0.700, 0.694); prognostic values of APOL3 and APOL6 were validated in HCCDB database (all P < 0.05). Differentially expressed APOL1 and APOL6 might be diagnostic biomarkers; APOL3 and APOL6 might be prognostic biomarkers of RFS and OS for HCC via chemokine signaling pathways.

Molecular characteristics and clinical implications of serine/arginine-rich splicing factors in human cancer

As critical splicing regulators, serine/arginine-rich splicing factors (SRSFs) play pivotal roles in carcinogenesis. As dysregulation of SRSFs may confer potential cancer risks, targeting SRSFs could provide important insights into cancer therapy. However, a global and comprehensive pattern to elaborate the molecular characteristics, mechanisms, and clinical links of SRSFs in a wide variety of human cancer is still lacking. In this study, a systematic analysis was conducted to reveal the molecular characteristics and clinical implications of SRSFs covering more than 10000 tumour samples of 33 human cancer types. We found that SRSFs experienced prevalent genomic alterations and expression perturbations in multiple cancer types. The DNA methylation, m6A modification, and miRNA regulation of SRSFs were all cancer context-dependent. Importantly, we found that SRSFs were strongly associated with cancer immunity, and were capable of predicting response to immunotherapy. And SRSFs had colossal potential for predicting survival in multiple cancer types, including those that have received immunotherapy. Moreover, we also found that SRSFs could indicate the drug sensitivity of targeted therapy and chemotherapy. Our research highlights the significance of SRSFs in cancer occurrence and development, and provides sufficient resources for understanding the biological characteristics of SRSFs, offering a new and unique perspective for developing cancer therapeutic strategies.

Diagnostic role and immune correlates of programmed cell death-related genes in hepatocellular carcinoma

Programmed cell death (PCD) is thought to have multiple roles in tumors. Here, the roles of PCD-related genes were comprehensively analyzed to evaluate their values in hepatocellular carcinoma (HCC) diagnosis and prognosis. Gene expression and single-cell data of HCC patients, and PCD-related genes were collected from public databases. The diagnostic and prognostic roles of differentially expressed PCD-related genes in HCC were explored by univariate and multivariate Cox regression analyses. Single-cell data were further analyzed for the immune cells and expression of feature genes. Finally, we evaluated the expression of genes by quantitative real-time polymerase chain reaction and Western blot, and the proportion of immune cells was detected by flow cytometry in HCC samples. We obtained 52 differentially expressed PCD-related genes in HCC, based on which the consensus clustering analysis cluster 2 was found to have a worse prognosis than cluster 1. Then 10 feature genes were identified using LASSO analysis, and programmed cell death index (PCDI) was calculated to divided HCC patients into high-PCDI and low-PCDI groups. Worse prognosis was observed in high-PCDI group. Cox regression analysis showed that PCDI is an independent prognostic risk factor for HCC patients. Additionally, SERPINE1 and G6PD of feature genes significantly affect patient survival. Macrophages and Tregs were significantly positively correlated with PCDI. G6PD mainly expressed in macrophages, SERPINE1 mainly expressed in fibroblast. The experimental results confirmed the high expression of SERPINE1 and G6PD in HCC compared with the control, and the infiltration level of macrophages and Treg in HCC was also obviously elevated. PCDI may be a new predictor for the diagnosis of patients with HCC. The association of SERPINE1 and G6PD with the immune environment will provide new clues for HCC therapy.

Association of Tumor Cell Metabolic Subtype and Immune Response With the Clinical Course of Hepatocellular Carcinoma

AIM

Tumor metabolism plays an important role in tumorigenesis and tumor progression. This study evaluated the potential association of tumor cell metabolism and immune cell tumor infiltration with the clinical course of hepatocellular carcinoma (HCC).

METHODS

Gene-wise normalization and principal component analysis were performed to evaluate the metabolic system. A tumor microenvironment score system of tumor immune cell infiltration was constructed to evaluate its association with metabolic subtypes. Finally, we analyzed the impact of metabolism and immune cell infiltration on the clinical course of HCC.

RESULTS

A total of 673 HCC patients were categorized into cholesterogenic (25.3%), glycolytic (14.6%), mixed (10.4%), and quiescent (49.8%) types based on glycolysis and cholesterol biosynthesis gene expression. The subgroups including the glycolytic genotyping expression (glycolytic and mixed types) showed a higher mortality rate. The glycolytic, cholesterogenic, and mixed types were positively correlated with M0 macrophage, resting mast cell, and naïve B-cell infiltration (P = .013, P = .019, and P = .006, respectively). In TCGA database, high CD8+ T cell and low M0 macrophage infiltration were associated with prolonged overall survival (OS, P = .0017 and P < .0001, respectively). Furthermore, in glycolytic and mixed types, patients with high M0 macrophage infiltration had a shorter OS (P = .03 and P = .013, respectively), and in quiescent type, patients with low naïve B-cell infiltration had a longer OS (P = .007).

CONCLUSIONS

Tumor metabolism plays a prognostic role and correlates with immune cell infiltration in HCC. M0 macrophage and CD8+ T cell appear to be promising prognostic biomarker for HCC. Finally, M0 macrophages may represent a useful immunotherapeutic target in patients with HCC.

Aberrant expression of cuproptosis‑related gene LIPT1 is associated with metabolic dysregulation of fatty acid and prognosis in hepatocellular carcinoma

PURPOSE

Lipoyltransferase 1 (LIPT1) has been recently identified as a cuproptosis‑related gene. As a key enzyme of lipoic acid metabolism, LIPT1 has been revealed to play important roles in hereditary diseases involved with lipoic acid biosynthesis defects, while its roles in hepatocellular carcinoma (HCC) remain to be elucidated. Hence, we aimed to explore the roles and mechanisms of LIPT1 in HCC progression.

METHODS

The expression of LIPT1 in HCC tissues and its clinical significance for HCC were evaluated by bioinformatic analysis and in our patient cohort. The influences of LIPT1 on the growth, migration, and lipid metabolism of HCC cells were assessed in vitro. The underlying mechanisms were explored using gene set enrichment analysis (GSEA) and molecular experiments.

RESULTS

LIPT1 expression was significantly elevated in HCC tissues compared to the normal tissues, and such upregulation was associated with more malignant pathological features and poor prognosis of patients with HCC. LIPT1 silencing significantly inhibited cell proliferation, migration, and lipid content. GSEA revealed that LIPT1 upregulation was significantly associated with various cancer-associated signaling pathways, including the PI3K-AKT signaling pathway and the Wnt/β-catenin pathway. Further molecular experiments indicated that LIPT1 silencing repressed the expression of peroxisome proliferator-activated receptor gamma (PPARγ) and inactivated the AKT/GSK-3β/β-catenin signaling axis.

CONCLUSIONS

Upregulation of LIPT1 is involved in metabolic dysregulation of fatty acid and poor prognosis of HCC patients, which suggests that LIPT1 plays an important role in reprogramming lipid metabolism and could act as a potential prognostic marker and therapeutic target for HCC.

Polo-like kinase-1 mediates hepatitis C virus-induced cell migration, a drug target for liver cancer

Polo-like kinase 1 (PLK1) is a regulator of cell mitosis and cytoskeletal dynamics. PLK1 overexpression in liver cancer is associated with tumour progression, metastasis, and vascular invasion. Hepatitis C virus (HCV) NS5A protein stimulates PLK1-mediated phosphorylation of host proteins, so we hypothesised that HCV-PLK1 interactions might be a mechanism for HCV-induced liver cancer. We used a HCV cell-culture model (Jc1) to investigate the effects of virus infection on the cytoskeleton. In HCV-infected cells, a novel posttranslational modification in β-actin was observed with phosphorylation at Ser239. Using in silico and in vitro approaches, we identified PLK1 as the mediating kinase. In functional experiments with a phosphomimetic mutant form of β-actin, Ser239 phosphorylation influences β-actin polymerization and distribution, resulting in increased cell motility. The changes were prevented by treating cells with the PLK1 inhibitor volasertib. In HCV-infected hepatocytes, increased cell motility contributes to cancer cell migration, invasion, and metastasis. PLK1 is an important mediator of these effects and early treatment with PLK1 inhibitors may prevent or reduce HCC progression, particularly in people with HCV-induced HCC.

Construction of a hepatocytes-related and protein kinase-related gene signature in HCC based on ScRNA-Seq analysis and machine learning algorithm

With recent advancements in single-cell sequencing and machine learning methods, new insights into hepatocellular carcinoma (HCC) progression have been provided. Protein kinase-related genes (PKRGs) affect cell growth, differentiation, apoptosis, and signaling during HCC progression, making the predictive relevance of PKRGs in HCC highly necessary for personalized medicine. In this study, we analyzed single-cell data of HCC and used the machine learning method of LASSO regression to construct PKRG prediction models in six major cell types. CDK4 and AURKB were found to be the best PKRG prognostic signature for predicting the overall survival of HCC patients (including TCGA, ICGC, and GEO datasets) in hepatocytes. Independent clinical factors were further screened out using the COX regression method, and a nomogram combining PKRGs and cancer status was created. Treatment with Palbociclib (CDK4 Inhibitor) and Barasertib (AURKB Inhibitor) inhibited HCC cell migration. Patients classified as PKRG high- or low-risk groups showed different tumor mutation burdens, immune infiltrations, and gene enrichment. The PKRG high-risk group showed higher tumor mutation burdens and gene set enrichment analysis indicated that cell cycle, base excision repair, and RNA degradation pathways were more enriched in these patients. Additionally, the PKRG high-risk group demonstrated higher infiltration levels of Naïve CD8+ T cells, Endothelial cells, M2 macrophage, and Tregs than the low-risk group. In summary, this study established the hepatocytes-related PKRG signature for prognostic stratification at the single-cell level by using machine learning algorithms in HCC and identified potential HCC treatment targets based on the PKRG signature.

Decreased B4GALT1 promotes hepatocellular carcinoma cell invasiveness by regulating the laminin-integrin pathway

Beta1,4-galactosyltransferases (B4GALTs) play a crucial role in several diseases, including cancer. B4GALT1 is highly expressed in the liver, and patients with mutations in B4GALT1 exhibit hepatopathy. However, the role of B4GALT1 in liver cancer remains unclear. Here, we found that B4GALT1 was significantly downregulated in hepatocellular carcinoma (HCC) tissue compared with the adjacent liver tissue, and low B4GALT1 expression was associated with vascular invasion and poor overall survival in patients with HCC. Additionally, silencing or loss of B4GALT1 enhanced HCC cell migration and invasion in vitro and promoted lung metastasis of HCC in NOD/SCID mice. Moreover, B4GALT1 knockdown or knockout increased cell adhesion to laminin, whereas B4GALT1 overexpression decreased the adhesion. Through a mass spectrometry-based approach and Griffonia simplicifolia lectin II (GSL-II) pull-down assays, we identified integrins α6 and β1 as the main protein substrates of B4GALT1 and their N-glycans were modified by B4GALT1. Further, the increased cell migration and invasion induced by B4GALT1 knockdown or knockout were significantly reversed using a blocking antibody against integrin α6 or integrin β1. These results suggest that B4GALT1 downregulation alters N-glycosylation and enhances the laminin-binding activity of integrin α6 and integrin β1 to promote invasiveness of HCC cells. Our findings provide novel insights into the role of B4GALT1 in HCC metastasis and highlight targeting the laminin-integrin axis as a potential therapeutic strategy for HCC with low B4GALT1 expression.

An integrative analysis reveals the prognostic value and potential functions of MTMR2 in hepatocellular carcinoma

Abnormal expression of myotubularin-related protein 2 (MTMR2) has been identified in certain types of cancer, leading to varying effects on tumor genesis and progression. However, the various biological significances of MTMR2 in hepatocellular carcinoma (HCC) have not been systematically and comprehensively studied. The aim of this study was to explore the role of MTMR2 in HCC. We obtained the raw data from Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Afterward, we analyzed the data using R and cBioPortal. We investigated the connection between MTMR2 and its expression, prognosis, clinical significance, methylation, genetic alterations, tumor microenvironment (TME), tumor mutation burden (TMB), and drug reactivity in HCC patients. MTMR2 expression levels in HCC cells were validated through western blotting and RT-qPCR. MTMR2 exhibits high levels of expression across a wide range of cancer types, including HCC. MTMR2 is diagnostically valuable in detecting HCC, with its up-regulated expression often being indicative of poor prognosis among HCC patients. The in vitro experiments confirmed elevated MTMR2 expression in HepG2, HUH-7, and MHCC-97H cells. Univariate and multivariate Cox analysis demonstrated that MTMR2 was an independent prognostic factor in HCC patients. The cg20195272 site has the highest degree of methylation in MTMR2, and it is positively correlated with MTMR2 expression. Patients with high levels of methylation at the cg20195272 site show poor prognosis. Analysis of the TME indicates that high expression of MTMR2 is associated with elevated ESTIMATE score and that MTMR2 expression correlates positively with infiltration by resting memory CD4 T cells, activated dendritic cells, as well as several immune checkpoints. There is a negative correlation between MTMR2 expression and TMB, and drug sensitivity analyses have shown that higher MTMR2 expression is associated with lower IC50 values. This study indicates that increased expression of MTMR2 may play a crucial role in the occurrence, progression, diagnosis, prognostic prediction and drug therapy of HCC.

Identification of subclusters and prognostic genes based on glycolysis/gluconeogenesis in hepatocellular carcinoma

Background

This study aimed to examine glycolysis/gluconeogenesis-related genes in hepatocellular carcinoma (HCC) and evaluate their potential roles in HCC progression and immunotherapy response.

Methods

Data analyzed in this study were collected from GSE14520, GSE76427, GSE174570, The Cancer Genome Atlas (TCGA), PXD006512, and GSE149614 datasets, metabolic pathways were collected from MSigDB database. Differentially expressed genes (DEGs) were identified between HCC and controls. Differentially expressed glycolysis/gluconeogenesis-related genes (candidate genes) were obtained and consensus clustering was performed based on the expression of candidate genes. Bioinformatics analysis was used to evaluate candidate genes and screen prognostic genes. Finally, the key results were tested in HCC patients.

Results

Thirteen differentially expressed glycolysis/gluconeogenesis-related genes were validated in additional datasets. Consensus clustering analysis identified two distinct patient clusters (C1 and C2) with different prognoses and immune microenvironments. Immune score and tumor purity were significantly higher in C1 than in C2, and CD4+ memory activated T cell, Tfh, Tregs, and macrophage M0 were higher infiltrated in HCC and C1 group. The study also identified five intersecting DEGs from candidate genes in TCGA, GSE14520, and GSE141198 as prognostic genes, which had a protective role in HCC patient prognosis. Compared with the control group, the prognostic genes all showed decreased expression in HCC patients in RT-qPCR and Western blot analyses. Flow cytometry verified the abnormal infiltration level of immune cells in HCC patients.

Conclusion

Results showed that glycolysis/gluconeogenesis-related genes were associated with patient prognosis, immune microenvironment, and response to immunotherapy in HCC. It suggests that the model based on five prognostic genes may valuable for predicting the prognosis and immunotherapy response of HCC patients.

The Application of Nano-drug Delivery System With Sequential Drug Release Strategies in Cancer Therapy

Currently, multidrug combinations are often used clinically to improve the efficacy of oncology chemotherapy, but multidrug combinations often lead to multidrug resistance and decreased performance, resulting in more severe side effects than monotherapy. Therefore, sequential drug release strategies in time and space as well as nano-carriers that respond to the tumor microenvironment have been developed. First, the advantage of the sequential release strategy is that they can load multiple drugs simultaneously to meet their spatiotemporal requirements and stability, thus exerting synergistic effects of two or more drugs. Second, in some cases, sequential drug delivery of different molecular targets can improve the sensitivity of cancer cells to drugs. Control the metabolism of cancer cells, and remodel tumor vasculature. Finally, some drug combinations with built-in release control are used for sequential administration. This paper focuses on the use of nanotechnology and built-in control device to construct drug delivery carriers with different stimulation responses, thus achieving the sequential release of drugs. Therefore, the nano-sequential delivery carrier provides a new idea and platform for the therapeutic effect of various drugs and the synergistic effect among drugs.

NCOA5 Haploinsufficiency in Myeloid-Lineage Cells Sufficiently Causes Nonalcoholic Steatohepatitis and Hepatocellular Carcinoma

BACKGROUND & AIMS

The nuclear receptor coactivator 5 (NCOA5) is a putative type 2 diabetes susceptibility gene. NCOA5 haploinsufficiency results in the spontaneous development of nonalcoholic fatty liver disease (NAFLD), insulin resistance, and hepatocellular carcinoma (HCC) in male mice; however, the cell-specific effect of NCOA5 haploinsufficiency in various types of cells, including macrophages, on the development of NAFLD and HCC remains unknown.

METHODS

Control and myeloid-lineage-specific Ncoa5 deletion (Ncoa5ΔM/+) mice fed a normal diet were examined for the development of NAFLD, nonalcoholic steatohepatitis (NASH), and HCC. Altered genes and signaling pathways in the intrahepatic macrophages of Ncoa5ΔM/+ male mice were analyzed and compared with those of obese human individuals. The role of platelet factor 4 (PF4) in macrophages and the underlying mechanism by which PF4 affects NAFLD/NASH were explored in vitro and in vivo. PF4 expression in HCC patient specimens and prognosis was examined.

RESULTS

Myeloid-lineage-specific Ncoa5 deletion sufficiently causes spontaneous NASH and HCC development in male mice fed a normal diet. PF4 overexpression in Ncoa5ΔM/+ intrahepatic macrophages is identified as a potent mediator to trigger lipid accumulation in hepatocytes by inducing lipogenesis-promoting gene expression. The transcriptome of intrahepatic macrophages from Ncoa5ΔM/+ male mice resembles that of obese human individuals. High PF4 expression correlated with poor prognosis of HCC patients and increased infiltrations of M2 macrophages, regulatory T cells, and myeloid-derived suppressor cells in HCCs.

CONCLUSIONS

Our findings reveal a novel mechanism for the onset of NAFLD/NASH and HCC initiated by NCOA5-deficient macrophages, suggesting the NCOA5-PF4 axis in macrophages as a potential target for developing preventive and therapeutic interventions against NAFLD/NASH and HCC.

Hepatocellular carcinomas, exhibiting intratumor fibrosis, express cancer-specific extracellular matrix remodeling and WNT/TGFB signatures, associated with poor outcome

BACKGROUND AND AIMS

HCC, the third leading cause of cancer-related death, arises in the context of liver fibrosis. Although HCC is generally poorly fibrogenic, some tumors harbor focal intratumor extracellular matrix (ECM) deposits called "fibrous nests." To date, the molecular composition and clinical relevance of these ECM deposits have not been fully defined.

APPROACH AND RESULTS

We performed quantitative matrisome analysis by tandem mass tags mass spectrometry in 20 human cancer specific matrisome (HCCs) with high or low-grade intratumor fibrosis and matched nontumor tissues, as well as in 12 livers from mice treated with vehicle, carbon tetrachloride, or diethylnitrosamine. We found 94 ECM proteins differentially abundant between high and low-grade fibrous nests, including interstitial and basement membrane components, such as several collagens, glycoproteins, proteoglycans, enzymes involved in ECM stabilization and degradation, and growth factors. Pathway analysis revealed a metabolic switch in high-grade fibrosis, with enhanced glycolysis and decreased oxidative phosphorylation. Integrating the quantitative proteomics with transcriptomics from HCCs and nontumor livers (n = 2,285 samples), we identified a subgroup of fibrous nest HCCs, characterized by cancer-specific ECM remodeling, expression of the WNT/TGFB (S1) subclass signature, and poor patient outcome. Fibrous nest HCCs abundantly expressed an 11-fibrous-nest - protein signature, associated with poor patient outcome, by multivariate Cox analysis, and validated by multiplex immunohistochemistry.

CONCLUSIONS

Matrisome analysis highlighted cancer-specific ECM deposits, typical of the WNT/TGFB HCC subclass, associated with poor patient outcomes. Hence, histologic reporting of intratumor fibrosis in HCC is of clinical relevance.

A robust panel based on genomic methylation sites for recurrence-free survival in early hepatocellular carcinoma

Purpose

Altered gene methylation precedes altered gene expression and the onset of disease. This study aimed to develop a potential model for predicting recurrence of early to mid-stage hepatocellular carcinoma (HCC) using methylation loci.

Methods

We used data from early to mid-stage HCC patients (TNM I-II) in the TCGA-LIHC dataset and lasso-cox regression model to identify an 18-DNA methylation site panel from which to calculate the riskScore of patients. The correlation of high/low riskScore with recurrence-free survival (RFS) and immune microenvironment in HCC patients was analyzed by bioinformatics. It was also validated in the GSE56588 dataset and the final dynamic nomogram was constructed.

Results

The results showed that riskScore was significantly correlated with RFS in HCC patients. The differential mutated genes between the two groups of HCC patients with high/low riskScore were mainly enriched in the TP53 signaling pathway. The immune microenvironment was better in HCC patients in the low-riskScore group compared to the high-riskScore group. This was validated in the GSE56588 dataset. Based on the subgroup stratification analysis of the relationship between high/low riskScore and RFS, as well as univariate and multivariate cox analyses, the riskScore was found to be independent of clinical indicators. We found that riskScore, vascular invasion and cirrhosis status could effectively differentiate RFS in HCC patients, and we also constructed prediction model based on these three factors. The model we constructed were validated in the TCGA-LIHC database and a web calculator was built for clinical use.

Conclusion

The methylation riskScore is a predictor of RFS independent of clinical factors and can be used as a marker to predict recurrence in HCC patients.

Integrative Evaluation of the Clinical Significance Underlying Protein Arginine Methyltransferases in Hepatocellular Carcinoma

HCC is a major contributor to cancer-related mortality worldwide. Curative treatments are available for a minority of patients diagnosed at early stages; however, only a few multikinase inhibitors are available and are marginally effective in advanced cases, highlighting the need for novel therapeutic targets. One potential target is the protein arginine methyltransferase, which catalyzes various forms of arginine methylation and is often overexpressed in various cancers. However, the diverse expression patterns and clinical values of PRMTs in HCC remain unclear. In the present study, we evaluated the transcriptional expression of PRMTs in HCC cohorts using publicly available datasets. Our results revealed a significant association between PRMTs and prognosis in HCC patients with diverse clinical characteristics and backgrounds. This highlights the promising potential of PRMTs as prognostic biomarkers in patients with HCC. In particular, single-cell RNA (scRNA) sequencing analysis coupled with another human cohort study highlighted the pivotal role of PRMT1 in HCC progression, particularly in the context of Tex. Translating these findings into specific therapeutic decisions may address the unmet therapeutic needs of patients with HCC.

MIF is a critical regulator of mononuclear phagocytic infiltration in hepatocellular carcinoma

Immunotherapy targeting tumor-associated macrophages (TAMs) is a promising approach to treating cancer. However, the limited drug targets and ambiguous mechanisms impede the development of clinical immunotherapy strategies. To elucidate the underlying processes involved in mononuclear phagocyte (MNP) infiltration and phenotypic changes in hepatocellular carcinoma (HCC), we integrated single-cell RNA-sequencing data from 100,030 cells derived from patients with HCC and healthy individuals and compared the phenotypes and origins of the MNPs in the tumor core, tumor periphery, adjacent normal tissue, and healthy liver samples. Using machine learning and multi-omics analyses, we identified 445 infiltration-associated genes and potential drug targets affecting this process. Through in vitro experiments, we found that the expression of macrophage migration inhibitory factor (MIF) is the upstream regulator of secreted phosphoprotein 1 (SPP1) and promote migration in TAMs. Our findings also indicate that MIF promotes tumor metastasis and invasion and is a promising potential target for treating HCC.

Prognostic model for hepatocellular carcinoma based on anoikis-related genes: immune landscape analysis and prediction of drug sensitivity

Background

Hepatocellular carcinoma (HCC) represents a complex ailment characterized by an unfavorable prognosis in advanced stages. The involvement of immune cells in HCC progression is of significant importance. Moreover, metastasis poses a substantial impediment to enhanced prognostication for HCC patients, with anoikis playing an indispensable role in facilitating the distant metastasis of tumor cells. Nevertheless, limited investigations have been conducted regarding the utilization of anoikis factors for predicting HCC prognosis and assessing immune infiltration. This present study aims to identify hepatocellular carcinoma-associated anoikis-related genes (ANRGs), establish a robust prognostic model for HCC, and delineate distinct immune characteristics based on the anoikis signature. Cell migration and cytotoxicity experiments were performed to validate the accuracy of the ANRGs model.

Methods

Consensus clustering based on ANRGs was employed in this investigation to categorize HCC samples obtained from both TCGA and Gene Expression Omnibus (GEO) cohorts. To assess the differentially expressed genes, Cox regression analysis was conducted, and subsequently, prognostic gene signatures were constructed using LASSO-Cox methodology. External validation was performed at the International Cancer Genome Conference. The tumor microenvironment (TME) was characterized utilizing ESTIMATE and CIBERSORT algorithms, while machine learning techniques facilitated the identification of potential target drugs. The wound healing assay and CCK-8 assay were employed to evaluate the migratory capacity and drug sensitivity of HCC cell lines, respectively.

Results

Utilizing the TCGA-LIHC dataset, we devised a nomogram integrating a ten-gene signature with diverse clinicopathological features. Furthermore, the discriminative potential and clinical utility of the ten-gene signature and nomogram were substantiated through ROC analysis and DCA. Subsequently, we devised a prognostic framework leveraging gene expression data from distinct risk cohorts to predict the drug responsiveness of HCC subtypes.

Conclusion

In this study, we have established a promising HCC prognostic ANRGs model, which can serve as a valuable tool for clinicians in selecting targeted therapeutic drugs, thereby improving overall patient survival rates. Additionally, this model has also revealed a strong connection between anoikis and immune cells, providing a potential avenue for elucidating the mechanisms underlying immune cell infiltration regulated by anoikis.

GBAP1 functions as a tumor promotor in hepatocellular carcinoma via the PI3K/AKT pathway

Hepatocellular carcinoma (HCC) is common worldwide, and novel therapeutic targets and biomarkers are needed to improve outcomes. In this study, bioinformatics analyses combined with in vitro and in vivo assays were used to identify the potential therapeutic targets. Differentially expressed genes (DEG) in HCC were identified by the intersection between The Cancer Genome Atlas and International Cancer Genome Consortium data. The DEGs were evaluated by a gene set enrichment analysis as well as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. A protein interaction network, univariate Cox regression, and Lasso regression were used to screen out hub genes correlated with survival. Increased expression of the long noncoding RNA GBAP1 in HCC was confirmed in additional datasets and its biological function was evaluated in HCC cell lines and nude mice. Among 121 DEGs, GBAP1 and PRC1 were identified as hub genes with significant prognostic value. Overexpression of GBAP1 in HCC was confirmed in 21 paired clinical tissues and liver cancer or normal cell lines. The inhibition of GBAP1 expression reduced HCC cell proliferation and promoted apoptosis by inactivating the PI3K/AKT pathway in vitro and in vivo. Therefore, GBAP1 has a pro-oncogenic function in HCC and is a candidate prognostic biomarker and therapeutic target.

Construction and validation of 3-genes hypoxia-related prognostic signature to predict the prognosis and therapeutic response of hepatocellular carcinoma patients

BACKGROUND

Previous studies have shown that the hypoxia microenvironment significantly impacted tumor progression. However, the clinical prognostic value of hypoxia-related risk signatures and their effects on the tumor microenvironment (TME) in hepatocellular carcinoma (HCC) remains hazy. This study aimed to conduct novel hypoxia-related prognostic signatures and improve HCC prognosis and treatment.

METHODS

Differentially expressed hypoxia-related genes (HGs) were identified with the gene set enrichment analysis (GSEA). Univariate Cox regression was utilized to generate the tumor hypoxia-related prognostic signature, which consists of 3 HGs, based on the least absolute shrinkage and selection operator (LASSO) algorithm. Then the risk score for each patient was performed. The prognostic signature's independent prognostic usefulness was confirmed, and systematic analyses were done on the relationships between the prognostic signature and immune cell infiltration, somatic cell mutation, medication sensitivity, and putative immunological checkpoints.

RESULTS

A prognostic risk model of four HGs (FDPS, SRM, and NDRG1) was constructed and validated in the training, testing, and validation datasets. To determine the model's performance in patients with HCC, Kaplan-Meier curves and time-dependent receiver operating characteristic (ROC) curves analysis was implemented. According to immune infiltration analysis, the high-risk group had a significant infiltration of CD4+ T cells, M0 macrophages, and dendritic cells (DCs) than those of the low-risk subtype. In addition, the presence of TP53 mutations in the high-risk group was higher, in which LY317615, PF-562271, Pyrimethamine, and Sunitinib were more sensitive. The CD86, LAIR1, and LGALS9 expression were upregulated in the high-risk subtype.

CONCLUSIONS

The hypoxia-related risk signature is a reliable predictive model for better clinical management of HCC patients and offers clinicians a holistic viewpoint when determining the diagnosis and course of HCC treatment.

Transcriptomic evidence for tumor-specific beneficial or adverse effects of TGFβ pathway inhibition on the prognosis of patients with liver cancer

Therapeutic targeting of the transforming growth factor beta (TGFβ) pathway in cancer represents a clinical challenge since TGFβ exhibits either tumor suppressive or tumor promoting properties, depending on the tumor stage. Thus, treatment with galunisertib, a small molecule inhibitor of TGFβ receptor type 1, demonstrated clinical benefits only in subsets of patients. Due to the functional duality of TGFβ in cancer, one can hypothesize that inhibiting this pathway could result in beneficial or adverse effects depending on tumor subtypes. Here, we report distinct gene expression signatures in response to galunisertib in PLC/PRF/5 and SNU-449, two cell lines that recapitulate human hepatocellular carcinoma (HCC) with good and poor prognosis, respectively. More importantly, integrative transcriptomics using independent cohorts of patients with HCC demonstrates that galunisertib-induced transcriptional reprogramming in SNU-449 is associated with human HCC with a better clinical outcome (i.e., increased overall survival), while galunisertib-induced transcriptional reprogramming in PLC/PRF/5 is associated with human HCC with a worse clinical outcome (i.e., reduced overall survival), demonstrating that galunisertib could indeed be beneficial or detrimental depending on HCC subtypes. Collectively, our study highlights the importance of patient selection to demonstrate a clinical benefit of TGFβ pathway inhibition and identifies Serpin Family F Member 2 (SERPINF2) as a putative companion biomarker for galunisertib in HCC.