Sorafenib for advanced hepatocellular carcinoma provides better prognosis after liver transplantation than without liver transplantation

A Cuproptosis-Related LncRNA Risk Model for Predicting Prognosis and Immunotherapeutic Efficacy in Patients with Hepatocellular Carcinoma

Cuproptosis is a novel programmed cell death pathway that is initiated by direct binding of copper to lipoylated tricarboxylic acid (TCA) cycle proteins. Recent studies have demonstrated that cuproptosis-related genes regulate tumorigenesis. However, the potential role and clinical significance of cuproptosis-related long noncoding RNAs (lncRNAs) in hepatocellular carcinoma (HCC) have not been established. We performed a bioinformatics analyses of RNA-sequencing data of HCC patients extracted from The Cancer Genome Atlas (TCGA) dataset to identify and validate a cuproptosis-related lncRNA prognostic signature. Furthermore, we analyzed the clinical significance of the prognostic signature of cuproptosis-related lncRNA in predicting the immunotherapeutic efficacy and the status of the tumor immune microenvironment. The RNA-sequencing data, genomic mutations, and clinical information were downloaded for 374 HCC samples and 50 normal liver samples from TCGA-Liver Hepatocellular Carcinoma (TCGA-LIHC) dataset. Co-expression analysis of Gene-lncRNA pairs with 49 known cuproptosis-related prognostic genes was used to define cuproptosis-related prognostic lncRNAs. We performed the LASSO algorithm and univariate and multivariate Cox regression analysis, respectively, to gradually identify the prognostic risk models of cuproptosis-related lncRNA based on the TCGA-LIHC dataset. Subsequently, the predictive performance of the model was evaluated using receiver operation characteristic (ROC) curves, Kaplan-Meier survival curves, and prognostic nomogram. The analysis of gene-lncRNA co-expression with 49 known cuproptosis-related genes identified 1359 cuproptosis-related lncRNAs in the TCGA-LIHC data set. A prognostic model was constructed with nine cuproptosis-related prognostic lncRNAs (AC007998.3, AC003086.1, AC009974.2, IQCH-AS1, LINC0256 1, AC105345.1, ZFPM2-AS1, AL353708.1 and WAC-AS1) using LASSO regression and Cox regression analyses. Risk scores were calculated for all HCC patient samples based on the four cuproptosis-related lncRNA prognostic models. All HCC patients were divided into high-risk and low-risk subgroups according to a 1:1 ratio column. The Kaplan-Meier survival curve analysis showed that the overall survival rate (OS) of the high-risk group patients was significantly lower than that of the low-risk group. The principal component analysis (PCA) confirmed that the prognostic lncRNA model accurately distinguished between high- and low-risk HCC patients. Furthermore, regression analysis as well as ROC curves confirmed the prognostic value of the risk score. A nomogram with risk scores and other clinicopathological characteristics was constructed. The nomogram accurately predicted the probability of 1-, 3-, and 5-year OS in HCC patients. Tumor mutation burden (TMB) scores were higher for high-risk patients than for low-risk patients. HCC patients in the low-risk group showed lower TIDE scores and greater sensitivity to antitumor drugs than those in the high-risk group. Tumor immune responses and tumor immune cell infiltration were significantly different between the high-risk and low-risk groups of patients with HCC. Our study identified a 9-cuproptosis-related lncRNA signature that accurately predicted prognosis, immunotherapeutic efficacy, and the status of the tumor immune microenvironment in HCC patients. Therefore, this cuproptosis-related lncRNA risk model is a potential prognostic biometric feature in HCC and shows high clinical value in identifying HCC patients who are potentially responsive to immunotherapy.

Recent advances in recurrent hepatocellular carcinoma therapy

Hepatocellular carcinoma (HCC) is the most prevalent form of primary liver cancer, accounting for 75%-85% of cases. Although treatments are given to cure early-stage HCC, up to 50%-70% of individuals may experience a relapse of the illness in the liver after 5 years. Research on the fundamental treatment modalities for recurrent HCC is moving significantly further. The precise selection of individuals for therapy strategies with established survival advantages is crucial to ensuring better outcomes. These strategies aim to minimize substantial morbidity, support good life quality, and enhance survival for patients with recurrent HCC. For individuals with recurring HCC after curative treatment, no approved therapeutic regimen is currently available. A recent study presented novel approaches, like immunotherapy and antiviral medication, to improve the prognosis of patients with recurring HCC with the apparent lack of data to guide the clinical treatment. The data supporting several neoadjuvant and adjuvant therapies for patients with recurring HCC are outlined in this review. We also discuss the potential for future clinical and translational investigations.

The Role of Ferroptosis and Cuproptosis in Curcumin against Hepatocellular Carcinoma

BACKGROUND

Among cancer-related deaths, hepatocellular carcinoma (HCC) ranks fourth, and traditional Chinese medicine (TCM) treatment is an important complementary alternative therapy for HCC. Curcumin is a natural ingredient extracted from Curcuma longa with anti-HCC activity, while the therapeutic mechanisms of curcumin remain unclear, especially on ferroptosis and cuproptosis.

METHODS

Differentially expressed genes (DEGs) of curcumin treatment in PLC, KMCH, and Huh7 cells were identified, respectively. The common genes among them were then obtained to perform functional enrichment analysis and prognostic analysis. Moreover, weighted gene co-expression network analysis (WGCNA) was carried out for the construction of the co-expression network. The ferroptosis potential index (FPI) and the cuproptosis potential index (CPI) were subsequently used to quantitatively analyze the levels of ferroptosis and cuproptosis. Finally, single-cell transcriptome analysis of liver cancer was conducted.

RESULTS

We first identified 702, 515, and 721 DEGs from curcumin-treated PLC, KMCH, and Huh7 cells, respectively. Among them, HMOX1, CYP1A1, HMGCS2, LCN2, and MTTP may play an essential role in metal ion homeostasis. By WGCNA, grey60 co-expression module was associated with curcumin treatment and involved in the regulation of ion homeostasis. Furthermore, FPI and CPI assessment showed that curcumin had cell-specific effects on ferroptosis and cuproptosis in different HCC cells. In addition, there are also significant differences in ferroptosis and cuproptosis levels among 16 HCC cell subtypes according to single-cell transcriptome data analysis.

CONCLUSIONS

We developed CPI and combined it with FPI to quantitatively analyze curcumin-treated HCC cells. It was found that ferroptosis and cuproptosis, two known metal ion-mediated forms of programmed cell death, may have a vital effect in treating HCC with curcumin, and there are significant differences in various liver cancer cell types and curcumin treatment which should be considered in the clinical application of curcumin.

Outcomes of Sorafenib for Recurrent Hepatocellular Carcinoma After Liver Transplantation in the Era of Combined and Sequential Treatments

BACKGROUND

Sorafenib and other tyrosine kinase inhibitors are the current standard of care for hepatocellular carcinoma (HCC) recurring after liver transplantation (LT). Sorafenib is sometimes regarded as a scarcely effective treatment in this setting because of some studies showing a short overall survival (OS) indirectly compared with historical series of nontransplanted patients. Additional data from multicenter prospective studies are needed before drawing definite conclusions.

METHODS

Retrospective analyses of a large prospective multicenter dataset of sorafenib-treated HCC patients to report the characteristics and outcomes of LT recipients (n = 81).

RESULTS

At the baseline, LT patients had key prognostic features (high prevalence of metastatic disease, and low prevalence of macrovascular invasion, α-fetoprotein >400 ng/mL, ALBI grade >1, performance status >0) that differentiated them from the typical populations of non-LT patient reported in clinical trials and observational studies. Moreover, a relevant proportion of LT patients received concurrent locoregional (12.3%) and postprogression systemic treatments (34.2%), resulting in a median OS of 18.7 mo.

CONCLUSIONS

Multimodal and sequential treatments are relatively frequent in post-LT HCC patients and contribute to a remarkable OS, together with favorable baseline characteristics. Despite the impossibility of matching with non-LT patients, our results indirectly suggest that the metastatic nature of post-LT recurrence and concurrent antirejection regimens should not discourage systemic treatments.

The m6A/m5C/m1A Regulated Gene Signature Predicts the Prognosis and Correlates With the Immune Status of Hepatocellular Carcinoma

RNA modification of m6A/m5C/m1A contributes to the occurrence and development of cancer. Consequently, this study aimed to investigate the functions of m6A/m5C/m1A regulated genes in the prognosis and immune microenvironment of hepatocellular carcinoma (HCC). The expression levels of 45 m6A/m5C/m1A regulated genes in HCC tissues were determined. The functional mechanisms and protein–protein interaction network of m6A/m5C/m1A regulated genes were investigated. The Cancer Genome Atlas (TCGA) HCC gene set was categorized based on 45 m6A/m5C/m1A regulated genes, and survival analysis was used to determine the relationship between the overall survival of HCC patients in subgroups. Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were used to construct the risk model and nomogram for m6A/m5C/m1A regulated genes. The relationships between m6A/m5C/m1A regulated gene subsets and risk model and immune cell infiltration were analyzed using CIBERSORT. m6A/m5C/m1A regulated genes were involved in mRNA and RNA modifications, mRNA and RNA methylation, mRNA and RNA stability, and other processes. There was a statistically significant difference between cluster1 and cluster2 groups of genes regulated by m6A/m5C/m1A. The prognosis of cluster1 patients was significantly better than that of cluster2 patients. There were statistically significant differences between the two cluster groups in terms of fustat status, grade, clinical stage, and T stage of HCC patients. The risk model comprised the overexpression of YBX1, ZC3H13, YTHDF1, TRMT10C, YTHDF2, RRP8, TRMT6, LRPPRC, and IGF2BP3, which contributed to the poor prognosis of HCC patients. The high-risk score was associated with prognosis, fustat status, grade, clinical stage, T stage, and M stage and was an independent risk factor for poor prognosis in HCC patients. High-risk score mechanisms included spliceosome, RNA degradation, and DNA replication, among others, and high-risk was closely related to stromal score, CD4 memory resting T cells, M0 macrophages, M1 macrophages, resting mast cells, CD4 memory activated T cells, and follicular helper T cells. In conclusion, the cluster subgroup and risk model of m6A/m5C/m1A regulated genes were associated with the poor prognosis and immune microenvironment in HCC and are expected to be the new tools for assessing the prognosis of HCC patients.

Predicting clinical trial outcomes using drug bioactivities through graph database integration and machine learning

The ability to estimate the probability of a drug to receive approval in clinical trials provides natural advantages to optimizing pharmaceutical research workflows. Success rates of clinical trials have deep implications for costs, duration of development, and under pressure due to stringent regulatory approval processes. We propose a machine learning approach that can predict the outcome of the trial with reliable accuracies, using biological activities, physicochemical properties of the compounds, target-related features, and NLP-based compound representation. In the above list, biological activities have never been used as an independent variable towards the prediction of clinical trial outcomes. We have extracted the drug-disease pair from clinical trials and mapped target(s) to that pair using multiple data sources. Empirical results demonstrate that ensemble learning outperforms independently trained, small-data ML models. We report results and inferences derived from a Random forest classifier with an average accuracy of 93%, and an F1 score of 0.96 for the "Pass" class. "Pass" refers to one of the two classes (Pass/Fail) of all clinical trials, and the model performed well in predicting the "Pass" category. Through the analysis of feature contributions to predictive capability, we have demonstrated that bioactivity plays a statistically significant role in predicting clinical trial outcome. A significant effort has gone into the production of the dataset that, for the first time, integrates clinical trial information with protein targets. Cleaned, organized, integrated data and code to map these entities, created as a part of this work, are available open-source. This reproducibility and the freely available code ensure that researchers with access to deep curated and proprietary clinical trial databases (we only use open-source data in this study) can further expand the scope of the results.

131I-Labeled Silk Fibroin Microspheres for Radioembolic Therapy of Rat Hepatocellular Carcinoma

Transarterial radioembolization (TARE) is a promising technology in hepatocellular carcinoma (HCC) therapy, which utilizes radionuclide-labeled microspheres to achieve arterial embolization and internal irradiation. However, the therapeutic effect of liver cancer can be affected by low radionuclide labeling rate and stability, as well as poor biocompatibility, and non-biodegradability of microspheres. Here, ¹³¹I-labeled silk fibroin microspheres (¹³¹I-SFMs) were developed as radioembolization material for effective TARE therapy against HCC. Silk fibroin rich in 10.03% of tyrosine was extracted from silkworm cocoons and then emulsified and genipin-crosslinked to prepare SFMs. SFMs show a good settlement rate, biodegradability, hemocompatibility, and low cytotoxicity. Afterward, ¹³¹I-SFMs were obtained by radiolabeling ¹³¹I onto the SFMs through the chloramine-T method. ¹³¹I-SFMs possess a high ¹³¹I labeling rate of over 84% and good radioactive stability and are thus conducive to internal radiotherapy. Significantly, ¹³¹I-SFMs with diameters around 11 μm were successfully radioembolized at the hepatic artery. ¹³¹I-SFMs were diffused in the liver, indicating the favorable biodistribution and biosafety in vivo. Based on the combination of embolization and local radiotherapy, the administration of ¹³¹I-SFMs shows a favorable inhibitive effect against the progression of HCC. Overall, the newly developed ¹³¹I-SFMs as radioembolization microspheres provide a promising application for effective TARE therapy against liver cancer.

Revealing the potential mechanism of Astragalus membranaceus improving prognosis of hepatocellular carcinoma by combining transcriptomics and network pharmacology

Background

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related death. Traditional Chinese medicine (TCM) has special advantages in relieving HCC, while Astragalus membranaceus is commonly used in TCM treatment. However, its underlying mechanisms for treatment of HCC are unclear.

Methods

Differentially expressed genes (DEGs) of Astragalus membranaceus treatment in HepG2 cells were identified, and Astragalus membranaceus-gene network was constructed. The hub genes were then obtained via protein-protein interaction (PPI) analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Gene Set Enrichment Analysis (GSEA) were subsequently performed. Furthermore, prognosis genes related to HCC from The Cancer Genome Atlas Program (TCGA) was identified to explore the correlation between Astragalus membranaceus treatment and prognosis of HCC. Finally, Astragalus membranaceus-component-target network was established through SymMap.

Results

Twenty five DEGs (15 up-regulated and 10 down-regulated) of Astragalus membranaceus treatment in HepG2 cells were identified. Among the 25 genes, MT1F, MT1G, MT1X and HMOX1 may play essential roles. Astragalus membranaceus mainly affects the Mineral absorption pathway in HCC. A total of 256 genes (p < 0.01) related to prognosis of HCC were identified, and MT1G is a common gene between prognosis genes and DEGs. Furthermore, Astragalus membranaceus may directly down-regulate MT1G through daidzein to promote ferroptosis of HCC cells and improve prognosis for HCC.

Conclusion

Our study provided new understandings of the pharmacological mechanisms by which Astragalus membranaceus improves the prognosis of HCC, and showed that the combination of transcriptomics and network pharmacology is helpful to explore mechanisms of TCM and traditional medicines from other nations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12906-021-03425-9.

Immunological Markers, Prognostic Factors and Challenges Following Curative Treatments for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortalities worldwide. Patients with early-stage HCC are eligible for curative treatments, such as surgical resection, liver transplantation (LT) and percutaneous ablation. Although curative treatments provide excellent long-term survival, almost 70–80% of patients experience HCC recurrence after curative treatments. Tumor-related factors, including tumor size, number and differentiation, and underlying liver disease, are well-known risk factors for recurrence following curative therapies. Moreover, the tumor microenvironment (TME) also plays a key role in the recurrence of HCC. Many immunosuppressive mechanisms, such as an increase in regulatory T cells and myeloid-derived suppressor cells with a decrease in cytotoxic T cells, are implicated in HCC recurrence. These suppressive TMEs are also modulated by several factors and pathways, including mammalian target of rapamycin signaling, vascular endothelial growth factor, programmed cell death protein 1 and its ligand 1. Based on these mechanisms and the promising results of immune checkpoint blockers (ICBs) in advanced HCC, there have been several ongoing adjuvant studies using a single or combination of ICB following curative treatments in HCC. In this review, we strive to provide biologic and immunological markers, prognostic factors, and challenges associated with clinical outcomes after curative treatments, including resection, LT and ablation.

The Outcomes of Systemic Treatment in Recurrent Hepatocellular Carcinomas Following Liver Transplants

BACKGROUND

Treatment of hepatocellular carcinoma (HCC) recurrences following liver transplant (LT) is challenging. Most clinical trials of systemic therapies for advanced HCC excluded patients with any history of organ transplant. We aimed to assess the outcomes in using various systemic therapies in patients with post-LT recurrence.

METHODS

Consecutive patients with HCC and recurrences following LT at a large tertiary centre from 2005 to 2018 were reviewed. Overall survival (OS), response rates and adverse events (AEs) were analysed.

RESULTS

Forty-three consecutive patients with a recurrence of HCC following LT were identified from 2005 to 2018. Median OS from diagnosis of recurrence was 17 months (CI 11.3, 22.7). Early recurrence within 12 months of transplant was associated with a significantly worse median survival of 10 months (CI 8.5, 11.4) compared to 26 months (CI 18.8, 33.2) when recurrences occurred after 12 months from transplant (p < 0.001) with a hazard ratio of 0.104 (log-rank test, p < 0.001). A total of 41 patients had received systemic therapies and 79.1% of them were on sorafenib as the first-line treatment. Among these patients treated with sorafenib, median OS from recurrence was 14 months (CI 7.3, 20.7). Hand-foot syndrome (34.7%) was most common among AEs followed by diarrhoea (26.7%). Overall, AEs led to dose interruptions in 8.8% of patients. Notably, 47.1% of patients received subsequent lines of systemic therapies after sorafenib.

CONCLUSIONS

Early recurrence within 1 year from transplant was the most significant risk factor. Treatment efficacy and adverse events and tolerability of sorafenib were comparable with those in the setting of advanced HCC without transplant.