Targeted Therapies for Hepatocellular Carcinoma Treatment: A New Era Ahead-A Systematic Review

From Inflammation to Oncogenesis: Tracing Serum DCLK1 and miRNA Signatures in Chronic Liver Diseases

Chronic liver diseases, fibrosis, cirrhosis, and HCC are often a consequence of persistent inflammation. However, the transition mechanisms from a normal liver to fibrosis, then cirrhosis, and further to HCC are not well understood. This study focused on the role of the tumor stem cell protein doublecortin-like kinase 1 (DCLK1) in the modulation of molecular factors in fibrosis, cirrhosis, or HCC. Serum samples from patients with hepatic fibrosis, cirrhosis, and HCC were analyzed via ELISA or NextGen sequencing and were compared with control samples. Differentially expressed (DE) microRNAs (miRNA) identified from these patient sera were correlated with DCLK1 expression. We observed elevated serum DCLK1 levels in fibrosis, cirrhosis, and HCC patients; however, TGF-β levels were only elevated in fibrosis and cirrhosis. While DE miRNAs were identified for all three disease states, miR-12136 was elevated in fibrosis but was significantly increased further in cirrhosis. Additionally, miR-1246 and miR-184 were upregulated when DCLK1 was high, while miR-206 was downregulated. This work distinguishes DCLK1 and miRNAs' potential role in different axes promoting inflammation to tumor progression and may serve to identify biomarkers for tracking the progression from pre-neoplastic states to HCC in chronic liver disease patients as well as provide targets for treatment.

P53/NANOG balance; the leading switch between poorly to well differentiated status in liver cancer cells

Enforcing a well-differentiated state on cells requires tumor suppressor p53 activation as a key player in apoptosis induction and well differentiation. In addition, recent investigations showed a significant correlation between poorly differentiated status and higher expression of NANOG. Inducing the expression of NANOG and decreasing p53 level switch the status of liver cancer cells from well differentiated to poorly status. In this review, we highlighted p53 and NANOG cross-talk in hepatocellular carcinoma (HCC) which is regulated through mitophagy and makes it a novel molecular target to attenuate cancerous phenotype in the management of this tumor.

Targeted cancer treatment using folate-conjugated sponge-like ZIF-8 nanoparticles: a review

ZIF-8 (zeolitic imidazolate framework-8) is a potential drug delivery system because of its unique properties, which include a large surface area, a large pore capacity, a large loading capacity, and outstanding stability under physiological conditions. ZIF-8 nanoparticles may be readily functionalized with targeting ligands for the identification and absorption of particular cancer cells, enhancing the efficacy of chemotherapeutic medicines and reducing adverse effects. ZIF-8 is also pH-responsive, allowing medication release in the acidic milieu of cancer cells. Because of its tunable structure, it can be easily functionalized to design cancer-specific targeted medicines. The delivery of ZIF-8 to cancer cells can be facilitated by folic acid-conjugation. Hence, it can bind to overexpressed folate receptors on the surface of cancer cells, which holds the promise of reducing unwanted deliveries. As a result of its importance in cancer treatment, the folate-conjugated ZIF-8 was the major focus of this review.

Albumin-Based Liver Reserve Models vs. MELD 3.0 in Prognostic Prediction for Hepatocellular Carcinoma Patients with Renal Insufficiency

The severity of liver functional reserve is an important prognostic predictor in hepatocellular carcinoma (HCC). The albumin-bilirubin (ALBI), easy (EZ)-ALBI, platelet-albumin-bilirubin (PALBI), platelet-albumin (PAL) score, and MELD 3.0 score are used to evaluate the severity of liver dysfunction. However, their prognostic role in HCC patients, specifically with renal insufficiency (RI), is unclear. We aimed to investigate the predictive accuracy of the five models in these patients. A total of 1120 newly diagnosed HCC patients with RI were enrolled. A multivariate Cox proportional analysis was used to identify independent predictors associated with survival. In the Cox model, older age, an α-fetoprotein ≥20 ng/mL, vascular invasion, a medium and high tumor burden score, poor performance status, a higher ALBI grade, an EZ-ALBI grade, a PALBI grade, a PAL grade, and MELD 3.0 score were all independently associated with decreased overall survival (all p < 0.001). Among the five liver reserve models, the ALBI grade is the best surrogate marker to represent liver functional reserve in terms of outcome prediction. The albumin-based liver reserve models (ALBI, EZ-ALBI, PALBI, and PAL) and MELD 3.0 are all feasible prognostic markers to indicate liver injury, specifically in HCC patients with RI. Among them, the ALBI grade is the most robust tool for survival prediction in these patients.

Associations Between Single Nucleotide Polymorphisms of Hypoxia-Related Genes and Capsule Formation in Hepatocellular Carcinoma

Purpose

Tumor capsule is an independent prognostic factor for patients with hepatocellular carcinoma (HCC) and used increasingly to guide clinical decision-making. Considering the genetic complexity for capsule formation and its potential association with hypoxia, the significance of the polymorphisms of hypoxia-related genes in capsule formation and HCC prognosis remains to be elucidated.

Patients and Methods

Peripheral blood samples from HCC patients were collected in this study. Single nucleotide polymorphism (SNP) genotyping was conducted by the iPLEX chemistry on a matrix-assisted laser desorption/ionization time-of-flight mass spectrometer (Sequenom, Inc.). The demographic and clinical data for the patients were obtained through medical chart review and/or consultation with the treating physicians. SPSS 25.0, R 4.1.1, and PLINK toolset were used to perform statistical analysis.

Results

A total of 183 patients were enrolled, including 88 patients assigned to the capsule group and 95 to the non-capsule group. SLC2A1 rs841858 T allele, SLC2A1 rs2297977 T allele, STAT1 rs1547550 C allele, and STAT1 rs34997637 G allele were associated with significantly increased risk of capsule formation. The genotypes of SLC2A1 rs841858, SLC2A1 rs2297977, STAT1 rs34997637, and STAT1 rs1914408 were significantly associated with the formation of HCC capsule. The polymorphisms of STAT1 rs2066802, STAT1 rs12693591, and HIF1A rs2057482 showed close relationship with the prognosis of HCC patients in the capsule group, while the genotype distributions of CTNNB1 rs4135385, IFNG rs1861494, and SERPINE1 rs2227631 were closely related to the survival of patients in the non-capsule group. Further haplotype analysis suggested that SLC2A1 block 1 and STAT1 block 2 were related to the susceptibility of HCC capsule.

Conclusion

The polymorphisms of the hypoxia-related genes (HIF1A, SERPINE1, IFNG, STAT1, CTNNB1, and SLC2A1) were correlated with the formation of HCC capsule. Several SNPs in these genes also showed association with HCC prognosis except SLC2A1. Further functional studies are warranted to explore the underlying mechanisms.

Development and Validation of a Novel Prognosis Model Based on a Panel of Three Immunogenic Cell Death-Related Genes for Non-Cirrhotic Hepatocellular Carcinoma

Purpose

The accurate prediction of non-cirrhotic hepatocellular carcinoma (NCHCC) risk facilitates improved surveillance strategy and decreases cancer-related mortality. This study aimed to explore the correlation between immunogenic cell death (ICD) and NCHCC prognosis using The Cancer Genome Atlas (TCGA) datasets, and the potential prognostic value of ICD-related genes in NCHCC.

Methods

Clinical and transcriptomic data of patients with NCHCC patients were retrieved from TCGA database. Weighted gene co-expression network analysis was performed to obtain the NCHCC phenotype-related module genes. Consensus clustering analysis was performed to classify the patients into two clusters based on intersection genes among differentially expressed genes (DEGs) between cancer and adjacent tissues, NCHCC phenotype-related genes, and ICD-related genes. NCHCC-derived tissue microarray was used to evaluate the correlation of the expression levels of key genes with NCHCC prognosis using immunohistochemical staining.

Results

Cox regression analyses were performed to construct a prognostic risk score model comprising three genes (TMC7, GRAMD1C, and GNPDA1) based on DEGs between two clusters. The model stratified patients with NCHCC into two risk groups. The overall survival (OS) of the high-risk group was significantly lower than that of the low-risk group. Univariable and multivariable Cox regression analyses revealed that these signature genes are independent predictors of OS. Functional analysis revealed differential immune status between the two risk groups. Next, a nomogram was constructed, which demonstrated the potent distinguishing ability of the developed model based on receiver operating characteristic curves. In vitro functional validation revealed that the migration and invasion abilities of HepG2 and Huh7 cells were upregulated upon GRAMD1C knockdown but downregulated upon TMC7 knockdown.

Conclusion

This study developed a prognostic model comprising three genes, which can aid in predicting the survival of patients with NCHCC and guide the selection of drugs and molecular markers for NCHCC.

PTEN-related risk classification models for predicting prognosis and immunotherapy response of hepatocellular carcinoma

INTRODUCTION

PTEN often mutates in tumors, and its manipulation is suggested to be used in the development of preclinical tools in cancer research. This study aims to explore the biological impact of gene expression related to PTEN mutations and to develop a prognostic classification model based on the heterogeneity of PTEN expression, and to explore its sensitivity as an indicator of prognosis and molecular and biologic features in hepatocellular carcinoma (HCC).

MATERIAL AND METHODS

RNA-seq data and mutation data of the LIHC cohort sample downloaded from The Cancer Genome Atlas (TCGA). The HCC samples were grouped according to the mean expression of PTEN, and the tumor microenvironment (TME) was evaluated by ESTIMATE and ssGSEA. The prognostic classification model related to PTEN were constructed by COX and LASSO regression analysis of differentially expressed genes (DEGs) between PTEN-high and -low expressed group.

RESULTS

The expression of PTEN was affected by copy number variation (CNV) and negatively correlated with immune score, IFNγ score and immune cell infiltration. 1281 DEGs were detected between PTEN-high and PTEN-low expressed group, 8 of the DEGs were finally filtered for developing a prognosis classification model. This model showed better prognostic value than other clinicopathological parameters, and the prediction accuracy of prognosis and ICB treatment for immunotherapy cohorts was better than that of TIDE model.

CONCLUSIONS

This study demonstrated the effect of CNV on PTEN expression and the negative immune correlation of PTEN, and constructed a classification model related to the expression of PTEN, which was of guiding significance for evaluating prognostic results of HCC patients and ICB treatment response of cancer immunotherapy cohorts.

Nucleoporin 107 is a prognostic biomarker in hepatocellular carcinoma associated with immune infiltration

OBJECTIVE

To assess the diagnostic value and clinical significance of nucleoporin 107 (NUP107) in hepatocellular carcinoma (HCC), and explore the possible mechanisms.

METHODS

The transcriptomic and clinical data of HCC patients were retrieved from The Cancer Genome Atlas (TCGA) and GEO databases. Tissue specimens were collected from HCC patients in the Guangxi area. According to the expression levels and prognostic characteristics of NUP107, ROC curves and nomogram models were constructed using the R package.

RESULTS

NUP107 was highly expressed in 26 human cancers including HCC, and was associated with advanced HCC staging and worse prognosis. NUP107 showed satisfactory ability to predict the prognosis of HCC patients (AUC >0.8). Results of gene set enrichment analysis (GSEA) further showed that NUP107 was mainly associated with cell cycle-related pathways such as the cell cycle, DNA replication, G2M checkpoint, E2F target, and mitotic spindle. In addition, NUP107 was also associated with immune infiltration in HCC and showed significant positive correlation with immune checkpoints (PD-L1 and TIM-3).

FDA-Approved Monoclonal Antibodies for Unresectable Hepatocellular Carcinoma: What Do We Know So Far?

Unresectable hepatocellular carcinoma (HCC) is an advanced primary liver malignancy with a poor prognosis. The Food and Drug Administration (FDA) has, to date, approved nivolumab, pembrolizumab, ramucirumab, nivolumab/ipilimumab, atezolizumab/bevacizumab, as well as tremelimumab/durvalumab, as first- or second-line monoclonal antibodies (mAbs) for unresectable HCC. The present review examines the current state of knowledge, and provides a useful update on the safety and efficacy of these therapeutic agents, thus attempting to define the suitability of each mAb for different patient subgroups.