Gene signature predictive of hepatocellular carcinoma patient response to transarterial chemoembolization

An Oxidative Stress-Related Prognostic Signature Predicts Treatment Response and Outcomes for Hepatocellular Carcinoma After Transarterial Chemoembolization

Purpose

Oxidative stress plays a critical role in promoting tumor resistance to hypoxia and chemotherapeutic drugs. However, the prognostic role of oxidative stress-related genes (OSRGs) in hepatocellular carcinoma (HCC) treated with transarterial chemoembolization (TACE) has not been fully explored.

Methods

We used transcriptome data from the GSE104580 cohort containing patients marked as responders or nonresponders to TACE therapy to identify differentially expressed OSRGs associated with TACE response (TR-OSRGs). We created a TR-OSRG prognostic signature based on TR-OSRGs using least absolute shrinkage and selection operator Cox and stepwise Cox regression analyses in a training cohort of patients with HCC (TCGA-LIHC). We verified this prognostic signature in two external cohorts of patients who received TACE for HCC (GSE14520-TACE and ZS-TACE-37). Finally, we constructed a prognostic nomogram model for predicting survival probability of patients with HCC based on Cox regression analysis.

Results

The TR-OSRG prognostic signature was created and shown to be a robust independent prognostic factor for treatment response and outcomes for HCC after TACE therapy. Risk scores based on this signature correlated with tumor stage and grade. Tumor samples from patients with higher risk scores exhibited more infiltration of immune cells and significantly increased expression of immune checkpoint genes. We also developed a nomogram for patients with HCC based on the TR-OSRG prognostic signature and clinical parameters; this nomogram was a useful quantitative analysis tool for predicting patient survival.

Conclusion

The TR-OSRGs signature exhibited good performance in predicting treatment response and outcomes in patients with HCC treated with TACE.

The crosstalk between cellular survival pressures and N6-methyladenosine modification in hepatocellular carcinoma

BACKGROUND

Within the tumor microenvironment, survival pressures are prevalent with potent drivers of tumor progression, angiogenesis, and therapeutic resistance. N6-methyladenosine (m6A) methylation has been recognized as a critical post-transcriptional mechanism regulating various aspects of mRNA metabolism. Understanding the intricate interplay between survival pressures and m6A modification provides new insights into the molecular mechanisms underlying hepatocellular carcinoma (HCC) progression and highlights the potential for targeting the survival pressures-m6A axis in HCC diagnosis and treatment.

DATA SOURCES

A literature search was conducted in PubMed, MEDLINE, and Web of Science for relevant articles published up to April 2024. The keywords used for the search included hepatocellular carcinoma, cellular survival, survival pressure, N6-methyladenosine, tumor microenvironment, stress response, and hypoxia.

RESULTS

This review delves into the multifaceted roles of survival pressures and m6A RNA methylation in HCC, highlighting how survival pressures modulate the m6A landscape, the impact of m6A modification on survival pressure-responsive gene expression, and the consequent effects on HCC cell survival, proliferation, metastasis, and resistance to treatment. Furthermore, we explored the therapeutic potential of targeting this crosstalk, proposing strategies that leverage the understanding of survival pressures and m6A RNA methylation mechanisms to develop novel, and more effective treatments for HCC.

CONCLUSIONS

The interplay between survival pressures and m6A RNA methylation emerges as a complex regulatory network that influences HCC pathogenesis and progression.

A cellular senescence-related signature for predicting prognosis, immunotherapy response, and candidate drugs in patients treated with transarterial chemoembolization (TACE)

BACKGROUND

Cellular senescence is essential to TME development, progression, and remodeling. Few studies have examined cellular senescence in HCC after TACE. Investigating the relationship between cellular senescence, post-TACE prognosis, the TME, and immune treatment responses is crucial.

METHODS

We analyzed the GSE104580 dataset to identify DEGs. A cellular senescence-related signature was developed using LASSO Cox regression in the GSE14520 dataset and validated in the ICGC dataset. High- and low-risk subgroups were compared using GSVA and GSEA. Correlation studies were conducted to explore the relationship between the prognostic model, immune infiltration, immunotherapy response, and drug sensitivity.

RESULTS

A cellular senescence-related signature comprising FOXM1, CDK1, CHEK1, and SERPINE1 was created and validated. High-risk patients showed significantly lower OS than low-risk patients. High-risk patients had carcinogenetic pathways activated, immunosuppressive cells infiltrated, and immunomodulatory genes overexpressed. They also showed higher sensitivity to EPZ004777_1237 and MK-2206_1053 and potential benefits from GSK-3 inhibitor IX, nortriptyline, lestaurtinib, and JNK-9L.

CONCLUSIONS

This study constructed a cellular senescence-related signature that could be used to predict HCC patients' responses to and prognosis after TACE treatment, aiding in the development of personalized treatment plans.

Molecular mechanisms of TACE refractoriness: Directions for improvement of the TACE procedure

Transcatheter arterial chemoembolisation (TACE) is the standard of care for intermediate-stage hepatocellular carcinoma and selected patients with advanced hepatocellular carcinoma. However, TACE does not achieve a satisfactory objective response rate, and the concept of TACE refractoriness has been proposed to identify patients who do not fully benefit from TACE. Moreover, repeated TACE is necessary to obtain an optimal and sustained anti-tumour response, which may damage the patient's liver function. Therefore, studies have recently been performed to improve the effectiveness of TACE. In this review, we summarise the detailed molecular mechanisms associated with TACE responsiveness and relapse after this treatment to provide more effective targets for adjuvant therapy while helping to improve TACE regimens.

Multiomics identifies metabolic subtypes based on fatty acid degradation allocating personalized treatment in hepatocellular carcinoma

BACKGROUND AND AIMS

Molecular classification is a promising tool for prognosis prediction and optimizing precision therapy for HCC. Here, we aimed to develop a molecular classification of HCC based on the fatty acid degradation (FAD) pathway, fully characterize it, and evaluate its ability in guiding personalized therapy.

APPROACH AND RESULTS

We performed RNA sequencing (RNA-seq), PCR-array, lipidomics, metabolomics, and proteomics analysis of 41 patients with HCC, in which 17 patients received anti-programmed cell death-1 (PD-1) therapy. Single-cell RNA sequencing (scRNA-seq) was performed to explore the tumor microenvironment. Nearly, 60 publicly available multiomics data sets were analyzed. The associations between FAD subtypes and response to sorafenib, transarterial chemoembolization (TACE), immune checkpoint inhibitor (ICI) were assessed in patient cohorts, patient-derived xenograft (PDX), and spontaneous mouse model ls. A novel molecular classification named F subtype (F1, F2, and F3) was identified based on the FAD pathway, distinguished by clinical, mutational, epigenetic, metabolic, and immunological characteristics. F1 subtypes exhibited high infiltration with immunosuppressive microenvironment. Subtype-specific therapeutic strategies were identified, in which F1 subtypes with the lowest FAD activities represent responders to compounds YM-155 and Alisertib, sorafenib, anti-PD1, anti-PD-L1, and atezolizumab plus bevacizumab (T + A) treatment, while F3 subtypes with the highest FAD activities are responders to TACE. F2 subtypes, the intermediate status between F1 and F3, are potential responders to T + A combinations. We provide preliminary evidence that the FAD subtypes can be diagnosed based on liquid biopsies.

CONCLUSIONS

We identified 3 FAD subtypes with unique clinical and biological characteristics, which could optimize individual cancer patient therapy and help clinical decision-making.

Identification of the key genes and mechanisms associated with transcatheter arterial chemoembolisation refractoriness in hepatocellular carcinoma

BACKGROUND

Transcatheter arterial embolisation (TACE) is the primary treatment for intermediate-stage hepatocellular carcinoma (HCC) patients while some HCC cases have shown resistance to TACE.

AIM

To investigate the key genes and potential mechanisms correlated with TACE refractoriness in HCC.

METHODS

The microarray datasets of TACE-treated HCC tissues, HCC and non-HCC tissues were collected by searching multiple public databases. The respective differentially expressed genes (DEGs) were attained via limma R package. Weighted gene co-expression network analysis was employed for identifying the significant modules related to TACE non-response. TACE refractoriness-related genes were obtained by intersecting up-regulated TACE-associated and HCC-associated DEGs together with the genes in significant modules related to TACE non-response. The key genes expression in the above two pairs of samples was compared respectively via Wilcoxon tests and standard mean differences model. The prognostic value of the key genes was evaluated by Kaplan-Meier curve. Multivariate analysis was utilised to investigate the independent prognostic factor in key genes. Single-cell RNA (scRNA) sequencing analysis was conducted to explore the cell types in HCC. TACE refractoriness-related genes activity was calculated via AUCell packages. The CellChat R package was used for the investigation of the cell-cell communication between the identified cell types.

RESULTS

HCC tissues of TACE non-responders (n = 66) and TACE responders (n = 81), HCC (n = 3941) and non-HCC (n = 3443) tissues were obtained. The five key genes, DLG associated protein 5 (DLGAP5), Kinesin family member 20A (KIF20A), Assembly factor for spindle microtubules (ASPM), Kinesin family member 11 (KIF11) and TPX2 microtubule nucleation factor (TPX2) in TACE refractoriness-related genes, were identified. The five key genes were all up-regulated in the TACE non-responders group and the HCC group. High expression of the five key genes predicted poor prognosis in HCC. Among the key genes, TPX2 was an independent prognostic factor. Four cell types, hepatocytes, embryonic stem cells, T cells and B cells, were identified in the HCC tissues. The TACE refractoriness-related genes expressed primarily in hepatocytes and embryonic stem cells. Hepatocytes, as the providers of ligands, had the strongest interaction with embryonic stem cells that provided receptors.

CONCLUSION

Five key genes (DLGAP5, KIF20A, ASPM, KIF11 and TPX2) were identified as promoting refractory TACE. Hepatocytes and embryonic stem cells were likely to boost TACE refractoriness.

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.

Outcomes of Transarterial Embolisation (TAE) vs. Transarterial Chemoembolisation (TACE) for Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

Although hepatocellular carcinoma is increasingly common, debate exists surrounding the management of patients with unresectable disease comparing transarterial embolisation (TAE) or transarterial chemoembolisation (TACE). This study aimed to compare the outcomes of patients receiving TAE and TACE. A systematic review was performed using PubMed, Medline, Embase, and Cochrane databases to identify randomised controlled trials (RCTs) until August 2021. The primary outcome was overall survival (OS) and the secondary outcomes were progression-free survival (PFS) and adverse events. Five studies with 609 patients were included in the analysis. There was no statistically significant difference in the OS (p = 0.36) and PFS (p = 0.81). There was no difference in OS among patients treated with a single TACE/TAE versus repeat treatments. Post-procedural adverse effects were higher in the TACE group but were not statistically significant. TACE has comparable long-term survival and complications profile to TAE for patients with HCC. However, the low-to-moderate quality of current RCTs warrants high-quality RCTs are necessary to provide enough evidence to give a definitive answer and inform treatment plans for the future.

Development and Validation of a Vascular Endothelial Growth Factor A-associated Prognostic Model for Unresectable Hepatocellular Carcinoma

Purpose

High serum vascular endothelial growth factor (VEGF) levels have been identified as an independent risk factor for hepatocellular carcinoma (HCC). We aimed to construct a VEGF-included prognostic model to accurately perform individualized predictions of survival probability for patients with unresectable HCC.

Patients and Methods

From October 2018 to March 2021, 182 consecutive newly diagnosed patients with unresectable HCC were retrospectively enrolled. Baseline serum VEGF-A and other characteristics were collected for all patients. Univariate Cox regression analysis and LASSO regression model were applied to develop the prognostic model, enhanced bootstrap method with 100 replicates was performed to validate its discrimination and calibration. We compared the final model with China Liver Cancer (CNLC) stage, American Joint Committee on Cancer (AJCC) stage, Barcelona Clinic Liver Cancer (BCLC) stage, and the model without the "VEGF". Finally, the established model was stratified by age.

Results

The VEGF-associated prognostic model we established has high accuracy with an overall C-index of 0.7892 after correction for optimistic estimates. The area under the curve (AUC) of the time-dependent receiver operating characteristic (ROC) curves at 6-month, 1-year, and 2-year after correction were 0.843, 0.860, 0.833, respectively, and the calibration of the model was 0.1153, 0.1514, and 0.1711, respectively. The final model showed significant improvement in predicting OS when compared to the other models according to Harrell's C-index, The AUC of the time-dependent ROC, area under the decision curve analysis (AUDC), integrated discrimination improvement (IDI), and continuous net reclassification index (NRI).

Conclusion

The VEGF-associated prognostic model may help to predict the survival probabilities of HCC patients with favorable performance and discrimination. However, further validation is required since we only verified this model using internal but not external data.

Differential expression of hepatic cancer stemness and hypoxia markers in residual cancer after locoregional therapies for hepatocellular carcinoma

Transarterial chemoembolization (TACE) and transarterial radioembolization (TARE) treatment to hepatocellular carcinoma (HCC) are effective tools to control tumor growth, prolong survival, palliate symptoms, and improve quality of life for patients with intermediate-stage HCC. Nevertheless, there is high variability of local HCC responses to locoregional therapies; therefore, better and personalized prediction of tumor response to TACE is necessary for management of patients with HCC, especially when these modalities of treatment are used to bridge patients for liver transplant. Here, we investigated differential expression of hepatic cancer stem cell and hypoxia in residual HCC after TACE treatment in comparison with TARE. A publicly available gene data set was screened for differentially expressed genes (DEGs) in TACE_Response compared with TACE_Non-response HCC. Analysis of the GSE104580 data set displayed a total of 406 DEGs, including 196 down-regulated and 210 up-regulated DEGs. Of the 196 down-regulated DEGs, three hepatic cancer stem cell (CSC) markers and 11 hypoxia-related genes were identified. Immunohistochemical staining of hepatic CSC and hypoxia markers on explant liver tissues exhibited more intense positive staining of hepatic CSC markers (CD24, EpCAM) and hypoxia marker carbonic anhydrase 9 (CA9) in residual tumor nodule from patients with HCC treated with TACE compared with nontreated patients. Furthermore, Pearson's correlation analysis revealed the significant correlation between hepatic CSC markers and hypoxia marker, CA9. Conclusion: Hepatic CSC and hypoxia markers predict nonresponse to TACE and are differentially expressed in residual tumor after TACE compared with TARE. In the long term, TACE-induced hypoxia may select an aggressive HCC phenotype.

Relationship between M6A methylation regulator and prognosis in patients with hepatocellular carcinoma after transcatheter arterial chemoembolization

Background

Patients with mid-stage HCC (hepatocellular carcinoma) may benefit from transcatheter arterial chemoembolization (TACE). However, patient efficacy varies widely, and the detailed assessment index is unknown. The most general methylation alteration in mRNA (Messenger RNA), N6-methyladenosine (m6A), is controlled by the m6A regulator, which is associated with the emergence of tumors. To include the molecular causes of cancer, competition with ceRNA (endogenous RNA) networks is crucial. However, the exact processes they contribute to TACE HCC remain uncertain. The purpose of this study was tantamount to investigating the possible function of ceRNA networks and m6A regulators in patients with TACE HCC.

Methods

Genes Associated with m6A were discovered using the TACE GEO (Gene Expression Omnibus) dataset. An additional estimate of M6A-associated DEGs (differentially expressed genes) was used to create a predictive response model, which is required. LncRNA-miRNA and miRNA-mRNA interactions were then predicted, the regulatory ceRNA network was set up using Cytoscape software, and target genes were identified using GEPIA online analysis. The connection between immunological checkpoints, immune cell marker genes, and target genes for immune cells was also examined.

Results

The detection of 4 m6A-associated DEGs, the development and evaluation of 2 Machine learning models, and the development of risk models that accurately predicted the response rate of specific patients. Additionally, we obtained two miRNAs (micro RNAs)and six lncRNAs (Long non-coding RNAs), forming an 8-pair ceRNA network, and the target gene LRPPRC deletion of one copy number and gene expression was highly correlated with the amount of Tregs immune cells. LRPPRC was related positively with NRP1, IRF5, and ITGAM and negatively with CCR7 and CD8B among immune cell marker genes. We also discovered that LRPPRC correlates positively with immune checkpoint CD274 cells.

Conclusion

The response of HCC patients to TACE therapy may be predicted using a model based on four gene expression data. We also developed a ceRNA network for TACE HCC related to m6A, which offered suggestions for more research into its molecular processes and possible prognostic indicators.

A Three-Gene Signature for Predicting the Prognosis of Patients Treated with Transarterial Chemoembolization (TACE) and Identification of PD-184352 as a Potential Drug to Reverse Nonresponse to TACE

Background

Transarterial chemoembolization (TACE) is a first-line treatment for patients with unresectable hepatocellular carcinoma (HCC). Owing to differences in its efficacy across individuals, determining the indicators of patient response to TACE and finding approaches to reversing nonresponse thereto are necessary.

Methods

Transcriptome data were obtained from the GSE104580 dataset, in which patients were marked as having TACE response or nonresponse. We identified differentially expressed genes (DEGs) and performed Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. We screened genes with a prognostic value for TACE in the HIF-1 signaling pathway by univariate regression analysis. By using least absolute shrinkage and selection operator (LASSO) Cox regression, we established a multigene signature in GSE14520, which we verified using a drug sensitivity test. The Connectivity Map (CMap) database was used to find potential drugs to reverse nonresponse to TACE.

Results

We constructed a prognostic signature consisting of three genes (erythropoietin (EPO), heme oxygenase 1 (HMOX1), and serine protease inhibitor 1 (SERPINE1)) that we validated by drug sensitivity test. After dividing patients treated with TACE into high- and low-risk groups based on this new signature, we showed that overall survival (OS) of the high-risk group was significantly lower than that of the low-risk group and that the risk score was an independent predictor of OS in patients treated with TACE. Based on our CMap findings, we speculated that PD-184352, an inhibitor of mitogen-activated protein kinase (MEK), had potential as a drug treatment to reverse nonresponse to TACE. We confirmed this speculation by using PD-184352 in a cell promotion experiment in a TACE environment.

Conclusion

We constructed a TACE-specific three-gene signature that could be used to predict HCC patients' responses to and prognosis after TACE treatment. PD-184352 might have potential as a drug to improve TACE efficacy.

Development and Validation of a Novel Circadian Rhythm-Related Signature to Predict the Prognosis of the Patients with Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most important causes of cancer-related deaths and remains a major public health challenge worldwide. Considering the extensive heterogeneity of HCC, more accurate prognostic models are imperative. The circadian genes regulate the daily oscillations of key biological processes, such as nutrient metabolism in the liver. Circadian rhythm disruption has recently been recognized as an independent risk factor for cancer. In this study, The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) were compared and 248 differentially expressed genes (DEGs) of the circadian rhythm were identified. HCC was classified into two subtypes based on these DEGs. The prognostic value of each circadian rhythm-associated gene (CRG) for survival was assessed by constructing a multigene signature from TCGA cohort. A 6-gene signature was created by applying the least absolute shrinkage and selection operator (LASSO) Cox regression method, and all patients in TCGA cohort were divided into high- and low-risk groups according to their risk scores. The survival rate of patients with HCC in the low-risk group was significantly higher than that in the high-risk group (p < 0.001). The patients with HCC in the Gene Expression Omnibus (GEO) cohort were also divided into two risk subgroups using the risk score of TCGA cohort, and the overall survival time (OS) was prolonged in the low-risk group (p = 0.012). Based on the clinical characteristics, the risk score was an independent predictor of OS in the patients with HCC. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses showed that multiple metabolic pathways, cell cycle, etc., were enhanced in the high-risk group. Using the metabolic pathway single-sample gene set enrichment analysis (ssGSEA), it was found that the metabolic pathways in the high- and low-risk groups between TCGA and GEO cohorts were altered essentially in the same way. In conclusion, the circadian genes play an important role in HCC metabolic rearrangements and can be further used to predict the prognosis the patients with HCC.

Distinct Gene Expression Profiles in Viable Hepatocellular Carcinoma Treated With Liver-Directed Therapy

Background

Hepatocellular carcinoma is a heterogeneous tumor that accumulates a mutational burden and dysregulated signaling pathways that differ from early to advanced stages. Liver transplant candidates with early-stage hepatocellular carcinoma (HCC) undergo liver-directed therapy (LDT) to delay disease progression and serve as a bridge to liver transplantation (LT). Unfortunately, &gt;80% of LDT-treated patients have viable HCC in the explant liver, dramatically increasing recurrence risk. Understanding the effect of LDT on early-stage HCC could help identify therapeutic targets to promote complete pathologic necrosis and improve recurrence-free survival. In this study, transcriptomic data from viable HCC in LDT-treated bridged to transplant patients were investigated to understand how treatment may affect tumor signaling pathways.

Methods

Multiplex transcriptomic gene analysis was performed with mRNA extracted from viable tumors of HCC patients bridged to transplant using LDT. The NanoString nCounter® Tumor Signaling 360 panel was used that contained 780 genes from 48 pathways involved in tumor biology within the microenvironment as well as antitumoral immune responses.

Results

Hierarchical clustering separated tumors into three subtypes (HCC-1, HCC-2, and HCC-3) each with distinct differences in anti-tumoral signaling and immune infiltration within the tumor microenvironment. Immune infiltration (neutrophils, T cells, and macrophages) were all lowest in subtype HCC-3. The tumor inflammatory signature consisting of 18 genes associated with PD-1/PD-L1 inhibition, antigen presentation, chemokine secretion, and adaptive immune responses was highest in subtype HCC-1 and lowest in HCC-3. History of decompensation and etiology were associated with HCC subtype favoring downregulations in inflammation and immune infiltration with upregulation of lipid metabolism. Gene expression among intrahepatic lesions was remarkably similar with &gt;85% of genes expressed in both lesions. Genes differentially expressed (&lt;8 genes per patient) in multifocal disease were all upregulated in LDT-treated tumors from pathways involving epithelial mesenchymal transition, extracellular matrix remodeling, and/or inflammation potentially implicating intrahepatic metastases.

Conclusion

Incomplete response to LDT may drive expression patterns that inhibit an effective anti-tumoral response through immune exclusion and induce intrahepatic spread.

Homogenous multifunctional microspheres induce ferroptosis to promote the anti-hepatocarcinoma effect of chemoembolization

Transcatheter arterial chemoembolization (TACE) is one of the main palliative therapies for advanced hepatocellular carcinoma (HCC), which is also regarded as a promising therapeutic strategy for cancer treatment. However, drug-loaded microspheres (DLMs), as commonly used clinical chemoembolization drugs, still have the problems of uneven particle size and unstable therapeutic efficacy. Herein, gelatin was used as the wall material of the microspheres, and homogenous gelatin microspheres co-loaded with adriamycin and Fe₃O₄ nanoparticles (ADM/Fe₃O₄-MS) were further prepared by a high-voltage electrospray technology. The introduction of Fe₃O₄ nanoparticles into DLMs not only provided excellent T2-weighted magnetic resonance imaging (MRI) properties, but also improved the anti-tumor effectiveness under microwave-induced hyperthermia. The results showed that ADM/Fe₃O₄-MS plus microwave irradiation had significantly better antitumor efficacy than the other types of microspheres at both cell and animal levels. Our study further confirmed that ferroptosis was involved in the anti-tumor process of ADM/Fe₃O₄-MS plus microwave irradiation, and ferroptosis marker GPX4 was significantly decreased and ACSL4 was significantly increased, and ferroptosis inhibitors could reverse the tumor cell killing effect caused by ADM/Fe₃O₄-MS to a certain extent. Our results confirmed that microwave mediated hyperthermia could amplify the antitumor efficacy of ADM/Fe₃O₄-MS by activating ferroptosis and the introduction of Fe₃O₄ nanoparticles can significantly improve TACE for HCC. This study confirmed that it was feasible to use uniform-sized gelatin microspheres co-loaded with Fe₃O₄ nanoparticles and adriamycin to enhance the efficacy of TACE for HCC.

Patient stratification in hepatocellular carcinoma: impact on choice of therapy

INTRODUCTION

HCC comprises around 60 to 80% of all primary liver cancers and exhibits wide geographical variability. Appropriate treatment allocation needs to include both patient and tumor characteristics.

AREAS COVERED

Current HCC classification systems to guide therapy are either liver function-centric and evaluate physiologic liver function to guide therapy or prognostic stratification classification systems broadly based on tumor morphologic parameters, patient performance status, and liver reserve assessment. This review focuses on different classification systems for HCC, their strengths, and weaknesses as well as the use of artificial intelligence in improving prognostication in HCC.

EXPERT OPINION

Future HCC classification systems will need to incorporate clinic-pathologic data from a multitude of sources and emerging therapies to develop patient-specific treatment plans targeting a patient's unique tumor profile.

Treatment and outcomes of hepatocellular carcinoma in patients with Sickle cell disease: a population-based study in the U.S

BACKGROUND

Sickle cell disease (SCD) is a rare hemoglobinopathy which can result in chronic liver disease and cirrhosis. Patients with SCD have an increased risk of hematologic malignancy, but the prevalence of hepatocellular carcinoma (HCC) in this population is unknown. Herein, the association of SCD with HCC was examined using registry data.

METHODS

The SEER-Medicare database was queried to identify patients diagnosed with HCC between 2000 and 2015, and further stratified by SCD status. Propensity matching was performed to examine cancer-related survival and treatment outcomes.

RESULTS

Overall 56,934 patients with HCC were identified, including 81 patients with SCD. Patients with SCD more frequently had cirrhosis [48.1% (39/81) vs 23.5% (13,377/56,853), p < 0.01] yet presented with smaller tumors [<5 cm: 51.9% (42/81) vs 38.5% (21,898/56,853), p = 0.01]. After propensity matching, SCD was not associated with attenuated survival (aHR 0.73 95%CI 0.52-1.01). When stratified by treatment, patients with SCD had equivalent outcomes to chemotherapy (p = 0.65), TACE/TARE (p = 0.35), resection (p = 0.15) and transplantation (p = 0.67) when compared to non-SCD patients.

CONCLUSION

This study confirms that a subset of patients with SCD will develop HCC. Importantly, therapeutic options for HCC should not be limited by pre-existing SCD, and similar survival should be expected when compared to non-SCD patients.

A 10-Gene Signature Identified by Machine Learning for Predicting the Response to Transarterial Chemoembolization in Patients with Hepatocellular Carcinoma

Background

Transarterial chemoembolization (TACE) is recommended for intermediate-stage HCC patients. Owing to substantial variation in its efficacy, indicators of patient responses to TACE need to be determined.

Methods

A Gene Expression Omnibus (GEO) dataset consisting of patients of different TACE-response status was retrieved. Differentially expressed genes (DEGs) were calculated and variable gene ontology analyses were conducted. Potential drugs and response to immunotherapy were predicted using multiple bioinformatic algorithms. We built and compared 5 machine-learning models with finite genes to predict patients' response to TACE. The model was also externally validated to discern different survival outcomes after TACE. Tumor-infiltrating lymphocytes (TILs) and tumor stemness index were evaluated to explore potential mechanism of our model.

Results

The gene set variation analysis revealed enhanced pathways related to G2/M checkpoint, E2F, mTORC1, and myc in TACE nonresponders. TACE responders had better immunotherapy response too. 373 DEGs were detected and the upregulated DEGs in nonresponders were enriched in IL-17 signal pathway. 5 machine-learning models were constructed and evaluated, and a linear support vector machine (SVM)-based model with 10 genes was selected (AQP1, FABP4, HERC6, LOX, PEG10, S100A8, SPARCL1, TIAM1, TSPAN8, and TYRO3). The model achieved an AUC and accuracy of 0.944 and 0.844, respectively, in the development cohort. In the external validation cohort comprised of patients receiving adjuvant TACE and postrecurrence TACE treatment, the predicted response group significantly outlived the predicted nonresponse counterparts. TACE nonresponders tend to have more macrophage M0 cells and lower resting mast cells in the tumor tissue and the stemness index is also higher than responders. Those characteristics were successfully captured by our model.

Conclusion

The model based on expression data of 10 genes could potentially predict HCC patients' response and prognosis after TACE treatment. The discriminating power was TACE-specific.

Nanomedicine Approach to Immunotherapy of Hepatocellular Carcinoma

In recent years, the growing studies focused on the immunotherapy of hepatocellular carcinoma and proved the preclinical and clinical promises of host antitumor immune response. However, there were still various obstacles in meeting satisfactory clinic need, such as low response rate, primary resistance and secondary resistance to immunotherapy. Tackling these barriers required a deeper understanding of immune underpinnings and a broader understanding of advanced technology. This review described immune microenvironment of liver and HCC which naturally decided the complexity of immunotherapy, and summarized recent immunotherapy focusing on different points. The ever-growing clues indicated that the instant killing of tumor cell and the subsequent relive of immunosuppressive microenvironment were both indis- pensables. The nanotechnology applied in immunotherapy and the combination with intervention technology was also discussed.

PKM2 inhibition may reverse therapeutic resistance to transarterial chemoembolization in hepatocellular carcinoma

BACKGROUND

Therapeutic options for patients with hepatocellular carcinoma (HCC) are limited. Transarterial chemoembolization (TACE) is an interventional procedure used to deliver chemotherapy and embolizing agents directly to the tumor and is the procedure of choice for patients with intermediate stage HCC. While effective, more than 40% of patients do not respond to therapy, highlighting the need to investigate possible mechanisms of resistance. We sought to evaluate mechanisms of TACE resistance and evaluate a potential therapeutic target to overcome this resistance.

METHODS

Using a prognostic gene signature which predicts TACE response (TACE Navigator) in a cohort of HCC patients who received TACE, patients were classified as responders and non-responders. Transcriptomic and gene pathway analysis were used to identify potential drivers of TACE resistance. Knockdown of the gene encoding rate limiting enzyme PKM2 using shRNA in HCC cell lines, as well as pharmacologic inhibition of PKM2 with shikonin using an in vitro TACE model measured response to chemotherapy under hypoxia. Finally, we replicated the TACE model with shikonin using patient derived cell line organoids (PDC). Functional studies were performed in vitro using immunoblotting, quantitative polymerase chain reaction, glycolysis and hypoxia assays.

RESULTS

In patient non-responders, we identified enrichment of the glycolysis pathway, specifically of the gene encoding the rate-limiting enzyme PKM2. We identified four HCC cell lines which recapitulated a TACE responder-like and non-responder-like phenotype. PKM2 knockdown in HCC cell lines demonstrated a less proliferative and aggressive phenotype as well as improved drug sensitivity to both doxorubicin and cisplatin. In vitro TACE model demonstrated that TACE non-responder-like cells overcame therapeutic resistance and rendered them susceptible to therapy through PKM2 knockdown. Lastly, we obtained similar results using a pharmacologic PKM2 inhibitor, shikonin in both cell lines, and PDC organoids.

CONCLUSION

Elevated PKM2 is associated with treatment resistance and abbreviated survival in patients receiving TACE. Elevated PKM2 in vitro is associated with increased utilization of the glycolysis pathway, resulting in oxygen independent cell metabolism. Through PKM2 knockdown as well as with pharmacologic inhibition with shikonin, non-responder cells can be reprogrammed to act as responders and could improve TACE efficacy in patients.